Social Security Analysis
Sith
2025-05-18
1 Descriptives
# Load required libraries
library(ggplot2)
library(tidyr)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(MCMCpack)## Loading required package: coda## Loading required package: MASS##
## Attaching package: 'MASS'## The following object is masked from 'package:dplyr':
##
## select## ##
## ## Markov Chain Monte Carlo Package (MCMCpack)## ## Copyright (C) 2003-2025 Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park## ##
## ## Support provided by the U.S. National Science Foundation## ## (Grants SES-0350646 and SES-0350613)
## ##library(ggpattern)
# Load the dataset
data = read.csv("ss_fund.csv")
# Reshape the data into long format for plotting
data_long = data %>%
pivot_longer(
cols = c(Income, Cost, Contributions, Reserves), # Columns to reshape
names_to = "Metric", # New column for metric names
values_to = "Value" # New column for values
)
# Ensure numeric conversion for the values
data_long$Value = as.numeric(gsub(",", "", data_long$Value)) / 1e3 # Convert to billions
# Create future years for projections
future_years = data.frame(Year = seq(max(data_long$Year) + 1, 2035))
# Function to generate projections for a given program and metric
generate_projections = function(program, metric, degree = 2) {
model = lm(Value ~ poly(Year, degree),
data = data_long %>% filter(Program == program, Metric == metric))
data.frame(
Year = future_years$Year,
Program = program,
Metric = metric,
Value = predict(model, newdata = future_years)
)
}
# Function to generate linear projections (for DI only)
generate_linear_projections = function(program, metric) {
model = lm(Value ~ Year,
data = data_long %>% filter(Program == program, Metric == metric))
data.frame(
Year = future_years$Year,
Program = program,
Metric = metric,
Value = predict(model, newdata = future_years)
)
}
# Generate projections for OASI (nonlinear)
oasi_projections = bind_rows(
generate_projections("OASI", "Reserves", degree = 3),
generate_projections("OASI", "Income", degree = 2),
generate_projections("OASI", "Cost", degree = 2),
generate_projections("OASI", "Contributions", degree = 2)
)
# Generate projections for DI (linear)
di_projections = bind_rows(
generate_linear_projections("DI", "Reserves"),
generate_linear_projections("DI", "Income"),
generate_linear_projections("DI", "Cost"),
generate_linear_projections("DI", "Contributions")
)
# Combine original data and projections
data_combined = bind_rows(data_long, oasi_projections, di_projections)
# Plot with line types to aid grayscale readability
ggplot(data_combined, aes(x = Year, y = Value, color = Metric, linetype = Metric)) +
geom_line(data = data_combined %>% filter(Year <= max(data_long$Year)), linewidth = 1) + # Original data
geom_line(data = data_combined %>% filter(Year > max(data_long$Year)),
linewidth = 1) + # Projections (same linetype)
facet_grid(factor(Program, levels = c("OASI", "DI")) ~ ., scales = "free_y") +
scale_x_continuous(breaks = seq(min(data_long$Year), 2035, by = 5)) +
scale_y_continuous(labels = scales::label_number(suffix = "B")) +
labs(
title = "OASI and DI Trust Fund: Historical Data and Projections (Through 2035)",
x = "Year",
y = "Value (Billions)",
color = "Metric",
linetype = "Metric"
) +
theme_minimal() +
theme(
legend.position = "bottom",
strip.text.y = element_text(face = "bold", size = 12),
axis.text.x = element_text(angle = 45, hjust = 1)
)
# DI as a Percent of OASDI
# Load required libraries
library(ggplot2)
library(dplyr)
# Data for DI % of OASDI
data = data.frame(
Year = c(1983:2024),
DI_Percent = c(
11.6, 8.8, 8.8, 8.8, 8.8, 8.7, 8.7, 9.7, 9.7, 9.7, 9.7, 15.2, 15.2, 15.2, 13.7, 13.7,
13.7, 14.5, 14.5, 14.5, 14.5, 14.5, 14.5, 14.5, 14.5, 14.5, 14.5, 14.5, 14.5, 14.5,
14.5, 14.5, 14.5, 19.1, 19.1, 19.1, 14.5, 14.5, 14.5, 14.5, 14.5, 14.5
)
)
# Calculate the drift model
# Connects the first point to the last point with a straight line
first_point = data$DI_Percent[1]
last_point = data$DI_Percent[nrow(data)]
drift_slope = (last_point - first_point) / (data$Year[nrow(data)] - data$Year[1])
data$Drift = first_point + drift_slope * (data$Year - data$Year[1])
# Plot the data with drift model
ggplot(data, aes(x = Year, y = DI_Percent)) +
geom_line(color = "blue", size = 1.2, aes(group = 1)) + # Original line
geom_line(aes(y = Drift), color = "darkred", linetype = "dotted", size = 1) + # Drift model
labs(
title = "DI as a Percent of OASDI Over Time (with Drift Model)",
x = "Year",
y = "DI Percent of OASDI"
) +
scale_x_continuous(breaks = seq(1983, 2024, by = 5)) + # 5-year ticks
scale_y_continuous(limits = c(0, 21), breaks = seq(0, 21, by = 3)) + # Set y-axis range and ticks
theme_minimal() +
theme(
plot.title = element_text(hjust = 0.5, size = 16, face = "bold"),
axis.text.x = element_text(angle = 45, hjust = 1)
)## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
# Max Taxable Earnings & National Average Wage Index
MaxTaxableEarnings = c(
rep(3000,14), rep(3600,4),rep(4200,4),
rep(4800,7), rep(6600,2), rep(7800, 4),
9000,10800,13200,14100,15300,16500,17700,
22900, 25900, 29700, 32400, 35700, 37800,
39600,42000, 43800, 45000, 48000, 51300,
53400, 55500, 57600, 60600,61200, 62700,
65400, 68400,72600, 76200, 80400,84900,
87000, 87900,90000, 94200, 97500, 102000,
106800, 106800, 106800, 110100, 113700, 117000,
118500, 118500, 127200, 128400, 132900, 137700,
142800, 147000, 160200, 168600
)
#CPI All Consumers, BLS
cpi_values = c(
21.67673611, 22.13794326, 22.45647482, 22.29607143, 21.23435374, 19.15,
18.04306358, 17.73551136, 17.34138889, 16.0074359, 13.99753363, 12.95207469,
13.11533613, 12.95207469, 12.00557692, 11.7790566, 11.69082397, 11.60390335,
11.64720149, 11.47591912, 11.10836299, 10.80086505, 10.7266323, 10.54543919,
10.43963211, 10.33592715, 10.20081699, 10.06919355, 9.909365079, 9.634104938,
9.345658683, 8.969683908, 8.505313351, 8.044974227, 7.707283951, 7.467583732,
7.030292793, 6.331541582, 5.801951673, 5.485852373, 5.150907591, 4.7875,
4.299517906, 3.788167476, 3.433938394, 3.234663212, 3.133985944, 3.004282964,
2.900975836, 2.848038321, 2.747755282, 2.638588335, 2.517298387, 2.388255547,
2.29181351, 2.224839629, 2.16017301, 2.106241565, 2.048195538, 1.98945188,
1.94482866, 1.915, 1.873619448, 1.812688734, 1.762535291, 1.735102835,
1.696440217, 1.652435151, 1.59828469, 1.548338294, 1.505459579, 1.449794011,
1.454970471, 1.431490076, 1.387687329, 1.359552079, 1.339925394, 1.31853626,
1.316973044, 1.300566233, 1.2734375, 1.243075661, 1.220952292, 1.206073158,
1.151954091, 1.066597188, 1.024427145, 1
)
# Calculate inflation-adjusted earnings
inflation_adjusted_earnings = MaxTaxableEarnings * cpi_values
years = 1937:2024
# Create a data frame
data = data.frame(Year = years,
Max_Taxable_Earnings = MaxTaxableEarnings,
Inflation_Adjusted_Earnings = inflation_adjusted_earnings)
# Plot the data
ggplot(data, aes(x = Year)) +
geom_line(aes(y = Max_Taxable_Earnings, color = "Max Taxable Earnings"), size = 1) +
geom_line(aes(y = Inflation_Adjusted_Earnings, color = "Inflation-Adjusted Max Taxable Earnings"), size = 1, linetype = "dashed") +
labs(
title = "Max Taxable Earnings & Inflation-Adjusted Max Taxable Earnings (2024 dollars)",
x = "Year",
y = "Earnings (USD)",
color = NULL
) +
theme_minimal() +
theme(
legend.position = "inside", # Use the inside option
legend.justification = c(0.1, 0.9)
)
# Tax Rates
# Load required libraries
library(ggplot2)
library(tidyr)
library(dplyr)
# Read the CSV file into R
data = read.csv("tax_rates.csv")
# Reshape the data to a long format for ggplot
data_long = data %>%
pivot_longer(
cols = -Year, # All columns except Year
names_to = "Variable", # New column for variable names
values_to = "Value" # New column for values
) %>%
mutate(
LineType = ifelse(grepl("\\.SE$", Variable), "Self-Employed", "Employed"), # Line types
ColorGroup = case_when(
grepl("OASI", Variable) ~ "OASI",
grepl("DI", Variable) ~ "DI",
grepl("Total", Variable) ~ "Total",
TRUE ~ "Other"
) # Grouping for colors
)
# Create the ggplot
ggplot(data_long, aes(x = Year, y = Value, color = ColorGroup, linetype = LineType)) +
geom_line(size = 1) +
labs(
title = "Social Security Tax Rates Over Time",
x = "Year",
y = "Tax Rate (%)",
color = "Tax Component",
linetype = "Type"
) +
scale_x_continuous(
limits = c(1937, 2024), # Set axis limits to truncate at 2024
breaks = seq(1940, 2024, by = 10) # Tick marks every decade
) +
theme_minimal() +
theme(
legend.position = "top",
legend.title = element_text(size = 12),
plot.title = element_text(hjust = 0.5, size = 16, face = "bold")
)
# Maximum Tax by Year over Time
# Load necessary libraries
library(ggplot2)
library(dplyr)
# Data for historical tax rates and CPI values
historical_data = data.frame(
Year = c(1937:2024),
EmployeeRate = c(
rep(0.02, 13), rep(0.03, 4), rep(0.04, 3), rep(0.045, 2), 0.05, 0.06, 0.06, 0.0625, rep(0.0725, 3),
0.077, 0.078, 0.076, 0.084, 0.084, 0.092, 0.092, 0.097, rep(0.099, 4), 0.101, 0.1016, 0.1016,
0.107, 0.108, 0.108, rep(0.114, 4), 0.1212, 0.1212, rep(0.124, 21), 0.104, 0.104, rep(0.124, 12)
)/2,
MaxTaxableEarnings = c(
rep(3000, 14), rep(3600, 4), rep(4200, 4),
rep(4800, 7), rep(6600, 2), rep(7800, 4),
9000, 10800, 13200, 14100, 15300, 16500, 17700,
22900, 25900, 29700, 32400, 35700, 37800,
39600, 42000, 43800, 45000, 48000, 51300,
53400, 55500, 57600, 60600, 61200, 62700,
65400, 68400, 72600, 76200, 80400, 84900,
87000, 87900, 90000, 94200, 97500, 102000,
106800, 106800, 106800, 110100, 113700, 117000,
118500, 118500, 127200, 128400, 132900, 137700,
142800, 147000, 160200, 168600
),
CPI = c(
21.67673611, 22.13794326, 22.45647482, 22.29607143, 21.23435374, 19.15,
18.04306358, 17.73551136, 17.34138889, 16.0074359, 13.99753363, 12.95207469,
13.11533613, 12.95207469, 12.00557692, 11.7790566, 11.69082397, 11.60390335,
11.64720149, 11.47591912, 11.10836299, 10.80086505, 10.7266323, 10.54543919,
10.43963211, 10.33592715, 10.20081699, 10.06919355, 9.909365079, 9.634104938,
9.345658683, 8.969683908, 8.505313351, 8.044974227, 7.707283951, 7.467583732,
7.030292793, 6.331541582, 5.801951673, 5.485852373, 5.150907591, 4.7875,
4.299517906, 3.788167476, 3.433938394, 3.234663212, 3.133985944, 3.004282964,
2.900975836, 2.848038321, 2.747755282, 2.638588335, 2.517298387, 2.388255547,
2.29181351, 2.224839629, 2.16017301, 2.106241565, 2.048195538, 1.98945188,
1.94482866, 1.915, 1.873619448, 1.812688734, 1.762535291, 1.735102835,
1.696440217, 1.652435151, 1.59828469, 1.548338294, 1.505459579, 1.449794011,
1.454970471, 1.431490076, 1.387687329, 1.359552079, 1.339925394, 1.31853626,
1.316973044, 1.300566233, 1.2734375, 1.243075661, 1.220952292, 1.206073158,
1.151954091, 1.066597188, 1.024427145, 1
)
)
# Compute raw and inflation-adjusted maximum tax
historical_data = historical_data %>%
mutate(
RawMaxTax = MaxTaxableEarnings * EmployeeRate , # Double for both employee and employer
InflationAdjustedMaxTax = RawMaxTax * CPI # Adjusted to 2024 dollars
)
# Create the ggplot
ggplot(historical_data, aes(x = Year)) +
geom_line(aes(y = RawMaxTax, color = "Raw Max Tax"), size = 1) +
geom_line(aes(y = InflationAdjustedMaxTax, color = "Inflation-Adjusted Max Tax"), size = 1, linetype = "dashed") +
labs(
title = "Max Social Security Tax Over Time (Raw and Inflation-Adjusted)",
x = "Year",
y = "Maximum Tax (USD)",
color = "Tax Type"
) +
scale_x_continuous(breaks = seq(1940, 2024, by = 10)) +
theme_minimal() +
theme(
plot.title = element_text(hjust = 0.5, size = 16, face = "bold"),
legend.position = "top"
)
2 Contour Plot of Taxed Benefit
library(ggplot2)
library(viridis)## Loading required package: viridisLitelibrary(metR) # For geom_text_contour
# Define the function to calculate taxable benefits
taxable_benefits = function(A, N, B, I) {
T1 = 25000 * I + 32000 * (1 - I)
T2 = 34000 * I + 44000 * (1 - I)
C = A + N + 0.5 * B
T_B = pmin(
0.85 * B,
0.5 * pmax(0, C - T1) + 0.35 * pmax(0, C - T2)
)
return(T_B)
}
# Generate data for individuals and couples
grid = expand.grid(
B = seq(0, 50000, length.out = 200),
A = seq(0, 100000, length.out = 200)
)
individual_data = grid
individual_data$T_B = with(individual_data, taxable_benefits(A, 0, B, I = 1))
couple_data = grid
couple_data$T_B = with(couple_data, taxable_benefits(A, 0, B, I = 0))
# Improved plot for Individuals
individual_plot = ggplot(individual_data, aes(x = B, y = A, z = T_B)) +
geom_tile(aes(fill = T_B)) +
geom_contour(color = "black", binwidth = 2000, size = 0.3) +
geom_text_contour(aes(label = after_stat(level)), binwidth = 5000, size = 3) +
scale_fill_viridis(name = "Taxable SS Benefits ($)", option = "plasma", direction = -1) +
labs(
title = "Taxable Social Security Benefits for Individuals",
subtitle = "Based on combined income and benefit amount",
x = "Annual SS Benefit (B, USD)",
y = "Other Income (A, USD)",
caption = "Up to 85% of benefits may be taxable depending on income levels"
) +
theme_minimal(base_size = 13) +
theme(
plot.title = element_text(face = "bold", size = 16),
legend.position = "right",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
)
# Improved plot for Couples
couple_plot = ggplot(couple_data, aes(x = B, y = A, z = T_B)) +
geom_tile(aes(fill = T_B)) +
geom_contour(color = "black", binwidth = 2000, size = 0.3) +
geom_text_contour(aes(label = after_stat(level)), binwidth = 5000, size = 3) +
scale_fill_viridis(name = "Taxable SS Benefits ($)", option = "plasma", direction = -1) +
labs(
title = "Taxable Social Security Benefits for Couples",
subtitle = "Based on combined income and benefit amount",
x = "Annual SS Benefit (B, USD)",
y = "Other Income (A, USD)",
caption = "Married filers face higher income thresholds before benefits are taxed"
) +
theme_minimal(base_size = 13) +
theme(
plot.title = element_text(face = "bold", size = 16),
legend.position = "right",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
)
# Display the plots
print(individual_plot)
print(couple_plot)
3 Individual Retirement Considerations
library(ggplot2)
library(readr)
library(dplyr)
library(viridis) # For beautiful color scales
library(metR)
library(ggrepel) # Optional for better contour label placement
# Read the PIA data
pia_data = read_csv("PIA.csv")## Rows: 279 Columns: 3
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (3): Income, Age, PIA
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.# Make sure columns are correctly named
# Expected columns: Income (in 1000s), Age, PIA (in 1000s)
# If not, rename appropriately:
# pia_data = rename(pia_data, Income = ..., Age = ..., PIA = ...)
# Create the plot
ggplot(pia_data, aes(x = Income, y = Age, z = PIA)) +
geom_tile(aes(fill = PIA), alpha = 0.9) +
geom_contour(color = "black", binwidth = 0.5) +
geom_text_contour(aes(label = after_stat(level)),
binwidth = 0.5,
color = "black",
size = 3,
stroke = 0.2) +
scale_fill_viridis(name = "PIA ($000s)", option = "viridis", direction = -1) +
scale_x_continuous(breaks = seq(10, 160, by = 10), name = "Average Annual Covered Earnings (in $000s)") +
scale_y_continuous(breaks = seq(62, 80, by = 1), expand = expansion(mult = c(0.02, 0.02))) +
labs(
title = "Social Security Primary Insurance Amount (PIA) by Retirement Age and Income",
subtitle = "Estimates assume full career earnings; benefits plateau after age 70",
caption = "PIA increases with average covered earnings and delayed retirement until age 70."
) +
theme_minimal(base_size = 13) +
theme(
plot.title = element_text(face = "bold", size = 16),
legend.position = "right",
axis.title.y = element_text(margin = margin(r = 10)),
axis.title.x = element_text(margin = margin(t = 10))
)
4 Libraries
require(EnvStats)## Loading required package: EnvStats##
## Attaching package: 'EnvStats'## The following object is masked from 'package:MASS':
##
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require(fpp3)## Loading required package: fpp3## Registered S3 method overwritten by 'tsibble':
## method from
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## ✖ MASS::select() masks dplyr::select()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorsrequire(magrittr)## Loading required package: magrittr
##
## Attaching package: 'magrittr'
##
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## set_names
##
## The following object is masked from 'package:tidyr':
##
## extractrequire(eia)## Loading required package: eia
## EIA_KEY not found. See `vignette("api", "eia")` for key storage options.5 Set Seed
set.seed(42)6 Read Data
6.1 3-Month TBill Compounding Factor by Year
## Index Year Inflation SSMin SS10. SSMedian SS90. SSMax
## 1 1 1937 0.971 0 27.84924 57.36264 92.15076 120.00
## 2 2 1938 1.028 0 27.84924 57.36264 92.15076 120.00
## 3 3 1939 1.000 0 27.84924 57.36264 92.15076 120.00
## 4 4 1940 0.993 0 27.84924 57.36264 92.15076 120.00
## 5 5 1941 0.901 0 27.84924 57.36264 92.15076 120.00
## 6 6 1942 0.910 0 27.84924 57.36264 92.15076 120.00
## 7 7 1943 0.970 0 27.84924 57.36264 92.15076 120.00
## 8 8 1944 0.977 0 27.84924 57.36264 92.15076 120.00
## 9 9 1945 0.978 0 27.84924 57.36264 92.15076 120.00
## 10 10 1946 0.819 0 27.84924 57.36264 92.15076 120.00
## 11 11 1947 0.912 0 27.84924 57.36264 92.15076 120.00
## 12 12 1948 0.970 0 27.84924 57.36264 92.15076 120.00
## 13 13 1949 1.021 0 27.84924 57.36264 92.15076 120.00
## 14 14 1950 0.941 0 41.77386 86.04396 138.22614 180.00
## 15 15 1951 0.940 0 50.12863 103.25275 165.87137 216.00
## 16 16 1952 0.992 0 50.12863 103.25275 165.87137 216.00
## 17 17 1953 0.993 0 50.12863 103.25275 165.87137 216.00
## 18 18 1954 1.007 0 66.83818 137.67034 221.16182 288.00
## 19 19 1955 0.996 0 77.97787 160.61539 258.02213 336.00
## 20 20 1956 0.970 0 77.97787 160.61539 258.02213 336.00
## 21 21 1957 0.971 0 87.72511 180.69232 290.27489 378.00
## 22 22 1958 0.982 0 87.72511 180.69232 290.27489 378.00
## 23 23 1959 0.983 0 111.39696 229.45056 368.60304 480.00
## 24 24 1960 0.986 0 133.67635 275.34067 442.32365 576.00
## 25 25 1961 0.993 0 133.67635 275.34067 442.32365 576.00
## 26 26 1962 0.987 0 139.24620 286.81320 460.75380 600.00
## 27 27 1963 0.984 0 161.52559 332.70331 534.47441 696.00
## 28 28 1964 0.990 0 161.52559 332.70331 534.47441 696.00
## 29 29 1965 0.981 0 161.52559 332.70331 534.47441 696.00
## 30 30 1966 0.965 0 235.88306 485.86156 780.51694 1016.40
## 31 31 1967 0.970 0 238.94648 492.17145 790.65352 1029.60
## 32 32 1968 0.953 0 275.15049 566.74288 910.44951 1185.60
## 33 33 1969 0.938 0 304.11370 626.40003 1006.28630 1310.40
## 34 34 1970 0.944 0 304.11370 626.40003 1006.28630 1310.40
## 35 35 1971 0.967 0 333.07691 686.05717 1102.12309 1435.20
## 36 36 1972 0.966 0 384.31951 791.60443 1271.68049 1656.00
## 37 37 1973 0.913 0 486.24773 1001.55169 1608.95227 2095.20
## 38 38 1974 0.877 0 606.55645 1249.35830 2007.04355 2613.60
## 39 39 1975 0.931 0 647.91257 1334.54182 2143.88743 2791.80
## 40 40 1976 0.951 0 703.05406 1448.11985 2326.34594 3029.40
## 41 41 1977 0.933 0 758.19556 1561.69787 2508.80444 3267.00
## 42 42 1978 0.910 0 829.76811 1709.11986 2745.63189 3575.40
## 43 43 1979 0.867 0 1079.91926 2224.37021 3573.36074 4653.28
## 44 44 1980 0.875 0 1221.39340 2515.77242 4041.48660 5262.88
## 45 45 1981 0.911 0 1475.03500 3038.21223 4880.76500 6355.80
## 46 46 1982 0.962 0 1624.16768 3345.38917 5374.23232 6998.40
## 47 47 1983 0.962 0 1789.59216 3686.12325 5921.60784 7711.20
## 48 48 1984 0.961 0 2000.13242 4119.78481 6618.26758 8618.40
## 49 49 1985 0.962 0 2095.37682 4315.96503 6933.42318 9028.80
## 50 50 1986 0.989 0 2222.36935 4577.53867 7353.63065 9576.00
## 51 51 1987 0.956 0 2317.61375 4773.71890 7668.78625 9986.40
## 52 52 1988 0.956 0 2531.49592 5214.26398 8376.50408 10908.00
## 53 53 1989 0.954 0 2700.26231 5561.88157 8934.93769 11635.20
## 54 54 1990 0.939 0 2952.57643 6081.58709 9769.82358 12722.40
## 55 55 1991 0.969 0 3073.44213 6330.54095 10169.75787 13243.20
## 56 56 1992 0.971 0 3194.30783 6579.49481 10569.69217 13764.00
## 57 57 1993 0.973 0 3315.17353 6828.44867 10969.62647 14284.80
## 58 58 1994 0.973 0 3487.83882 7184.09703 11540.96118 15028.80
## 59 59 1995 0.975 0 3522.37187 7255.22671 11655.22812 15177.60
## 60 60 1996 0.967 0 3608.70452 7433.05089 11940.89548 15549.60
## 61 61 1997 0.983 0 3764.10328 7753.13442 12455.09672 16219.20
## 62 62 1998 0.984 0 3936.76857 8108.78279 13026.43143 16963.20
## 63 63 1999 0.973 0 4178.49997 8606.69051 13826.30003 18004.80
## 64 64 2000 0.966 0 4385.69831 9033.46855 14511.90168 18897.60
## 65 65 2001 0.984 0 4627.42972 9531.37626 15311.77028 19939.20
## 66 66 2002 0.976 0 4886.42765 10064.84881 16168.77235 21055.20
## 67 67 2003 0.981 0 5007.29335 10313.80267 16568.70665 21576.00
## 68 68 2004 0.967 0 5059.09294 10420.49718 16740.10706 21799.20
## 69 69 2005 0.966 0 5179.95864 10669.45104 17140.04136 22320.00
## 70 70 2006 0.975 0 5421.69004 11167.35876 17939.90996 23361.60
## 71 71 2007 0.959 0 5611.62186 11558.57196 18568.37814 24180.00
## 72 72 2008 0.999 0 5870.61979 12092.04451 19425.38021 25296.00
## 73 73 2009 0.973 0 6146.88425 12661.08190 20339.51575 26486.40
## 74 74 2010 0.985 0 6146.88425 12661.08190 20339.51575 26486.40
## 75 75 2011 0.970 0 6146.88425 12661.08190 20339.51575 26486.40
## 76 76 2012 0.983 0 6336.81607 13052.29511 20967.98393 27304.80
## 77 77 2013 0.985 0 6544.01441 13479.07315 21653.58558 28197.60
## 78 78 2014 0.992 0 6733.94623 13870.28635 22282.05377 29016.00
## 79 79 2015 0.993 0 6820.27888 14048.11054 22567.72112 29388.00
## 80 80 2016 0.979 0 6820.27888 14048.11054 22567.72112 29388.00
## 81 81 2017 0.979 0 7321.00821 15079.49080 24224.59179 31545.60
## 82 82 2018 0.981 0 7390.07433 15221.75015 24453.12567 31843.20
## 83 83 2019 0.977 0 7649.07226 15755.22270 25310.12774 32959.20
## 84 84 2020 0.986 0 7925.33672 16324.26009 26224.26328 34149.60
## 85 85 2021 0.993 0 8218.86771 16928.86232 27195.53229 35414.40
## 86 86 2022 0.935 0 8460.59911 17426.77003 27995.40089 36456.00
## 87 87 2023 0.966 0 9220.32638 18991.62285 30509.27362 39729.60
## ThreeMoTBill TenYrTreas RetirementAge MaxTaxBracket Bend1 Bend2 BendF1
## 1 1.002418 1.0268 66.00 6000 0 0 0
## 2 1.000615 1.0256 66.00 6000 0 0 0
## 3 1.000407 1.0236 66.00 6000 0 0 0
## 4 1.000292 1.0221 66.00 6000 0 0 0
## 5 1.001035 1.0195 66.00 6000 0 0 0
## 6 1.003380 1.0246 66.00 6000 0 0 0
## 7 1.003800 1.0247 66.00 6000 0 0 0
## 8 1.003800 1.0248 66.00 6000 0 0 0
## 9 1.003800 1.0237 66.00 6000 0 0 0
## 10 1.003800 1.0219 66.00 6000 0 0 0
## 11 1.005567 1.0225 66.00 6000 0 0 0
## 12 1.010431 1.0244 66.00 6000 0 0 0
## 13 1.011135 1.0231 66.00 6000 0 0 0
## 14 1.011998 1.0232 66.00 6000 0 0 0
## 15 1.015134 1.0257 66.00 7200 0 0 0
## 16 1.017162 1.0268 66.00 7200 0 0 0
## 17 1.018705 1.0283 66.00 7200 0 0 0
## 18 1.009245 1.0248 66.00 7200 0 0 0
## 19 1.016711 1.0261 66.17 8400 0 0 0
## 20 1.026122 1.0290 66.33 8400 0 0 0
## 21 1.032201 1.0346 66.50 8400 0 0 0
## 22 1.016096 1.0309 66.67 8400 0 0 0
## 23 1.033347 1.0402 66.83 9600 0 0 0
## 24 1.028075 1.0472 67.00 9600 0 0 0
## 25 1.023520 1.0384 67.00 9600 0 0 0
## 26 1.027725 1.0408 67.00 9600 0 0 0
## 27 1.031493 1.0383 67.00 9600 0 0 0
## 28 1.035453 1.0417 67.00 9600 0 0 0
## 29 1.039463 1.0419 67.00 9600 0 0 0
## 30 1.048528 1.0461 67.00 13200 0 0 0
## 31 1.042841 1.0458 67.00 13200 0 0 0
## 32 1.053315 1.0553 67.00 15600 0 0 0
## 33 1.066427 1.0604 67.00 15600 0 0 0
## 34 1.063447 1.0779 67.00 15600 0 0 0
## 35 1.042986 1.0624 67.00 15600 0 0 0
## 36 1.040326 1.0595 67.00 18000 0 0 0
## 37 1.069548 1.0646 67.00 21600 0 0 0
## 38 1.078139 1.0699 67.00 26400 0 0 0
## 39 1.057599 1.0750 67.00 28200 0 0 0
## 40 1.049671 1.0774 67.00 30600 0 0 0
## 41 1.052350 1.0721 67.00 33000 0 0 0
## 42 1.071318 1.0796 67.00 35400 0 0 0
## 43 1.100164 1.0910 67.00 45800 180 1085 230
## 44 1.111025 1.1080 67.00 51800 194 1171 248
## 45 1.139227 1.1257 67.00 59400 211 1274 270
## 46 1.103715 1.1459 67.00 64800 230 1388 294
## 47 1.085995 1.1046 67.00 71400 254 1528 324
## 48 1.094962 1.1167 67.00 75600 267 1612 342
## 49 1.074630 1.1138 67.00 79200 280 1691 358
## 50 1.059454 1.0919 67.00 84000 297 1790 379
## 51 1.057692 1.0708 67.00 87600 310 1866 396
## 52 1.066207 1.0867 67.00 90000 319 1922 407
## 53 1.081017 1.0909 67.00 96000 339 2044 433
## 54 1.074857 1.0821 67.00 102600 356 2145 455
## 55 1.053415 1.0809 67.00 106800 370 2230 473
## 56 1.034104 1.0703 67.00 111000 387 2333 495
## 57 1.029968 1.0660 67.00 115200 401 2420 513
## 58 1.041756 1.0575 67.00 121200 422 2545 539
## 59 1.054863 1.0778 67.00 122400 426 2567 544
## 60 1.050051 1.0565 67.00 125400 437 2635 559
## 61 1.050602 1.0658 67.00 130800 455 2741 581
## 62 1.047639 1.0554 67.00 136800 477 2875 609
## 63 1.046306 1.0472 67.00 145200 505 3043 645
## 64 1.058115 1.0666 67.00 152400 531 3202 679
## 65 1.032003 1.0516 67.00 160800 561 3381 717
## 66 1.015905 1.0504 67.00 169800 592 3567 756
## 67 1.010053 1.0405 67.00 174000 606 3653 774
## 68 1.013045 1.0415 67.00 175800 612 3689 782
## 69 1.031061 1.0422 67.00 180000 627 3779 801
## 70 1.047212 1.0442 67.00 188400 656 3955 838
## 71 1.042967 1.0476 67.00 195000 680 4100 869
## 72 1.009203 1.0374 67.00 204000 711 4288 909
## 73 1.001317 1.0252 67.00 213600 744 4483 950
## 74 1.001327 1.0373 67.00 213600 761 4586 972
## 75 1.000346 1.0339 67.00 213600 749 4517 957
## 76 1.000823 1.0197 67.00 220200 767 4624 980
## 77 1.000538 1.0191 67.00 227400 791 4768 1011
## 78 1.000310 1.0286 67.00 234000 816 4917 1042
## 79 1.000350 1.0188 67.00 237000 826 4980 1056
## 80 1.003096 1.0209 67.00 237000 856 5157 1093
## 81 1.008952 1.0243 67.00 254400 885 5336 1131
## 82 1.019171 1.0258 67.00 256800 895 5397 1144
## 83 1.020334 1.0271 67.00 265800 926 5583 1184
## 84 1.001903 1.0176 67.00 275400 960 5785 1226
## 85 1.000411 1.0108 67.00 285600 996 6002 1272
## 86 1.013244 1.0176 67.00 294000 1024 6172 1308
## 87 1.050605 1.0353 67.00 320400 1115 6721 1425
## BendF2 BendF3 AvgPayout MaxPayout AvgPayIn MaxPayIn
## 1 0 0 0.00 0.0 23.160 120.00
## 2 0 0 0.00 0.0 21.280 120.00
## 3 0 0 0.00 0.0 22.480 120.00
## 4 0 0 0.00 0.0 24.040 120.00
## 5 0 0 0.00 0.0 29.360 120.00
## 6 0 0 0.00 0.0 37.600 120.00
## 7 0 0 0.00 0.0 45.680 120.00
## 8 0 0 0.00 0.0 49.040 120.00
## 9 0 0 0.00 0.0 50.240 120.00
## 10 0 0 0.00 0.0 51.640 120.00
## 11 0 0 0.00 0.0 53.960 120.00
## 12 0 0 0.00 0.0 58.240 120.00
## 13 0 0 0.00 0.0 56.600 120.00
## 14 0 0 0.00 0.0 92.460 180.00
## 15 0 0 0.00 0.0 102.780 216.00
## 16 0 0 0.00 0.0 108.000 216.00
## 17 0 0 0.00 0.0 112.500 216.00
## 18 0 0 0.00 0.0 148.880 288.00
## 19 0 0 0.00 0.0 156.880 336.00
## 20 0 0 0.00 0.0 165.440 336.00
## 21 0 0 0.00 0.0 193.410 378.00
## 22 0 0 0.00 0.0 195.840 378.00
## 23 0 0 0.00 0.0 227.400 480.00
## 24 0 0 0.00 0.0 280.200 576.00
## 25 0 0 0.00 0.0 287.760 576.00
## 26 0 0 0.00 0.0 314.125 600.00
## 27 0 0 0.00 0.0 377.435 696.00
## 28 0 0 0.00 0.0 399.040 696.00
## 29 0 0 0.00 0.0 425.720 696.00
## 30 0 0 0.00 0.0 485.870 1016.40
## 31 0 0 0.00 0.0 522.600 1029.60
## 32 0 0 0.00 0.0 553.432 1185.60
## 33 0 0 0.00 0.0 663.264 1310.40
## 34 0 0 0.00 0.0 708.624 1310.40
## 35 0 0 0.00 0.0 826.344 1435.20
## 36 0 0 1948.20 4860.0 897.920 1656.00
## 37 0 0 1997.04 6300.0 1044.302 2095.20
## 38 0 0 2258.52 6324.0 1158.696 2613.60
## 39 0 0 2486.16 7044.0 1255.320 2791.80
## 40 0 0 2698.32 7548.0 1364.220 3029.40
## 41 0 0 2916.00 8460.0 1491.336 3267.00
## 42 0 0 3158.40 10212.0 1690.942 3575.40
## 43 332 433 3531.60 10654.8 1880.006 4653.28
## 44 358 467 4096.80 11559.6 2074.062 5262.88
## 45 390 508 4631.64 12142.8 2422.052 6355.80
## 46 425 554 5031.60 12944.4 2594.592 6998.40
## 47 468 610 5289.24 13424.4 2748.384 7711.20
## 48 493 643 5526.84 14391.6 3171.936 8618.40
## 49 517 675 5743.44 14964.0 3367.788 9028.80
## 50 548 714 5861.28 15370.8 3534.684 9576.00
## 51 571 745 6151.80 15454.8 3705.456 9986.40
## 52 588 767 6441.24 15610.8 4233.516 10908.00
## 53 626 816 6802.20 16008.0 4527.790 11635.20
## 54 656 856 7230.72 16668.0 4870.472 12722.40
## 55 682 890 7551.84 16884.0 4978.848 13243.20
## 56 714 931 7831.68 17074.8 5229.328 13764.00
## 57 740 966 8088.72 17772.0 5386.064 14284.80
## 58 779 1016 8368.08 18084.0 5592.400 15028.80
## 59 785 1024 8637.60 18432.0 5845.360 15177.60
## 60 806 1052 8939.52 18672.0 6129.568 15549.60
## 61 839 1094 9298.08 18732.0 6427.168 16219.20
## 62 880 1147 9356.28 18960.0 6814.792 16963.20
## 63 931 1214 9651.60 18420.0 7083.872 18004.80
## 64 980 1278 10133.76 18432.0 7571.192 18897.60
## 65 1034 1349 10493.28 18504.0 7819.440 19939.20
## 66 1092 1424 10740.00 19020.0 7880.448 21055.20
## 67 1118 1458 11064.96 19884.0 8091.000 21576.00
## 68 1129 1472 11458.68 19968.0 8469.944 21799.20
## 69 1156 1508 12024.00 20220.0 8836.240 22320.00
## 70 1210 1578 12532.80 21228.0 9379.856 23361.60
## 71 1255 1636 12943.20 22068.0 9808.400 24180.00
## 72 1312 1711 13834.80 22860.0 10118.648 25296.00
## 73 1372 1789 13971.60 26220.0 9739.208 26486.40
## 74 1403 1830 14106.00 28152.0 10050.448 26486.40
## 75 1382 1803 14742.84 28392.0 10569.512 26486.40
## 76 1415 1845 15139.32 30156.0 10967.056 27304.80
## 77 1459 1903 15525.96 30396.0 11003.016 28197.60
## 78 1505 1962 15942.96 31704.0 11471.984 29016.00
## 79 1524 1987 16101.24 31956.0 11913.424 29388.00
## 80 1578 2058 16321.56 32244.0 12138.112 29388.00
## 81 1633 2130 16849.80 32244.0 12642.544 31545.60
## 82 1651 2154 17535.72 33456.0 13220.880 31843.20
## 83 1708 2228 18034.20 34332.0 13773.672 32959.20
## 84 1770 2309 18529.80 36132.0 14671.432 34149.60
## 85 1837 2395 19896.36 37776.0 15973.680 35414.40
## 86 1889 2463 21901.68 40140.0 16238.048 36456.00
## 87 2056 2682 22884.00 43524.0 16998.416 39729.607 Methods
# Required packages
library(tidyverse)
library(gtools)##
## Attaching package: 'gtools'## The following object is masked from 'package:psych':
##
## logit## The following objects are masked from 'package:MCMCpack':
##
## ddirichlet, rdirichletlibrary(gridExtra)##
## Attaching package: 'gridExtra'## The following object is masked from 'package:dplyr':
##
## combinelibrary(grid)##
## Attaching package: 'grid'## The following object is masked from 'package:metR':
##
## as.path# Matrix of ratings
ratings <- tribble(
~Construct, ~ChatGPT, ~Claude, ~Gemini, ~Copilot,
"ICB", 4, -5, 2, -2,
"E", 4, -2, -1, -4,
"T", -1, -2, -1, -3,
"S", -3, 1, -2, -4,
"AF", -1, -5, 2, 0,
"PV", -1, 1, -4, 4
)
# Sample Dirichlet weights
set.seed(42)
construct_weights <- rdirichlet(1, rep(1, 6)) %>% as.numeric() %>% round(3)
llm_weights <- rdirichlet(1, rep(1, 4)) %>% as.numeric() %>% round(3)
ratings$Weight <- construct_weights
# Melt for plotting
ratings_long <- ratings %>%
pivot_longer(cols = ChatGPT:Copilot, names_to = "LLM", values_to = "Rating")
# Ensure ordering matches the layout
ratings_long$Construct <- factor(ratings_long$Construct, levels = rev(ratings$Construct))
# Plain matrix (text only)
matrix_plot <- ggplot(ratings_long, aes(x = LLM, y = Construct)) +
geom_tile(color = "black", fill = "white") +
geom_text(aes(label = Rating), size = 5) +
theme_minimal() +
labs(title = "LLM Ratings by Construct (Text Only)", x = "LLM", y = "Construct") +
theme(panel.grid = element_blank())
# Construct weight bars
construct_bar <- tibble(
Construct = rev(ratings$Construct),
Weight = rev(ratings$Weight)
)
bar_right <- ggplot(construct_bar, aes(x = Weight, y = Construct)) +
geom_bar(stat = "identity", fill = "grey20") +
theme_minimal() +
labs(x = "Construct Weight", y = NULL) +
theme(axis.text.y = element_blank(), axis.ticks.y = element_blank())
# LLM weight bars
llm_bar <- tibble(
LLM = names(ratings)[2:5],
Weight = llm_weights
)
bar_top <- ggplot(llm_bar, aes(x = LLM, y = Weight)) +
geom_bar(stat = "identity", fill = "grey20") +
theme_minimal() +
labs(y = "LLM Weights") +
scale_y_continuous(breaks = c(0, 0.5, 1)) +
theme(
axis.title.x = element_blank(),
axis.text.y = element_text(size = 8)
)
# Combine the matrix + bar plots
grid.arrange(
bar_top,
arrangeGrob(matrix_plot, bar_right, ncol = 2, widths = c(4, 1)),
heights = c(1, 5)
)
8 Descriptives
library(psych)
library(ggplot2)
library(tidyr)
library(knitr)
library(kableExtra)
# Read your data
df <- read.csv("finalscores1029.csv")
# Get descriptive stats
desc <- describe(df)
# Get descriptive statistics
desc <- describe(df[, 1:25])
# Calculate IQR manually
iqr_vals <- apply(df[,1:25], 2, IQR, na.rm = TRUE)
# Build formatted table with selected stats
summary_table <- data.frame(
Variable = rownames(desc),
Min = round(desc$min, 2),
Median = round(desc$median, 2),
`Mean (SD)` = sprintf("%.2f (%.2f)", desc$mean, desc$sd),
Max = round(desc$max, 2),
IQR = round(iqr_vals, 2)
)
# Render with kableExtra
summary_table %>%
kbl(
caption = "Summary Statistics for Evaluation Scores (Including IQR)",
col.names = c("Variable", "Min", "Median", "Mean (SD)", "Max", "IQR"),
format = "html", # Change to "latex" for PDF output
booktabs = TRUE,
align = "lccccr"
) %>%
kable_styling(bootstrap_options = c("striped", "condensed", "hover", "responsive"),
full_width = FALSE, position = "center")| Variable | Min | Median | Mean (SD) | Max | IQR | |
|---|---|---|---|---|---|---|
| ICB1 | ICB1 | -5.00 | -2.00 | -0.90 (1.98) | 4.00 | 2.75 |
| ICB2 | ICB2 | -5.00 | -1.00 | -0.82 (2.29) | 3.00 | 4.75 |
| ICB3 | ICB3 | -5.00 | -1.00 | -0.75 (1.37) | 2.00 | 2.00 |
| ICB4 | ICB4 | -5.00 | 0.00 | -0.40 (2.08) | 3.00 | 4.00 |
| T1 | T1 | -4.00 | -1.00 | -0.94 (1.84) | 5.00 | 2.00 |
| T2 | T2 | -5.00 | -1.00 | -0.54 (2.02) | 3.00 | 3.00 |
| T3 | T3 | -5.00 | 0.00 | -0.81 (1.39) | 2.00 | 2.00 |
| T4 | T4 | -5.00 | -2.00 | -0.77 (2.45) | 4.00 | 4.75 |
| E1 | E1 | -4.00 | 0.00 | -0.02 (2.18) | 5.00 | 4.00 |
| E2 | E2 | -4.00 | 2.00 | 0.82 (2.24) | 4.00 | 4.00 |
| E3 | E3 | -4.00 | 0.00 | 0.46 (1.28) | 3.00 | 1.00 |
| E4 | E4 | -4.00 | -2.00 | -0.58 (1.97) | 3.00 | 3.00 |
| S1 | S1 | -3.00 | 2.00 | 1.22 (2.12) | 4.00 | 3.00 |
| S2 | S2 | -5.00 | 2.00 | 1.58 (2.33) | 5.00 | 5.00 |
| S3 | S3 | -5.00 | 2.00 | 1.23 (1.52) | 4.00 | 2.00 |
| S4 | S4 | -2.00 | 3.00 | 2.42 (1.81) | 5.00 | 2.00 |
| AF1 | AF1 | -3.00 | 2.00 | 1.87 (1.57) | 5.00 | 2.00 |
| AF2 | AF2 | -3.00 | 3.00 | 2.63 (1.01) | 5.00 | 1.00 |
| AF3 | AF3 | -4.00 | 0.00 | 0.49 (1.10) | 2.00 | 1.00 |
| AF4 | AF4 | -4.00 | 2.00 | 1.59 (2.29) | 5.00 | 3.00 |
| PV1 | PV1 | -5.00 | -1.00 | -0.82 (2.26) | 5.00 | 4.00 |
| PV2 | PV2 | -5.00 | -2.00 | -1.01 (2.42) | 3.00 | 5.00 |
| PV3 | PV3 | -5.00 | -1.00 | -0.89 (1.26) | 2.00 | 2.00 |
| PV4 | PV4 | -5.00 | -1.00 | -0.34 (2.59) | 4.00 | 6.00 |
| SS_Effect | SS_Effect | -1.48 | 0.37 | 0.64 (0.96) | 4.13 | 1.07 |
8.1 Boxplots
# Define constructs and LLMs
constructs <- c("ICB", "T", "E", "S", "AF", "PV")
llm_ids <- 1:4
llm_labels <- c("ChatGPT", "Claude", "Gemini", "Copilot")
# Build column names correctly
target_cols <- c()
for (construct in constructs) {
for (id in llm_ids) {
col_name <- paste0(construct, id)
if (col_name %in% colnames(df)) {
target_cols <- c(target_cols, col_name)
}
}
}
# Add COA column for reference
target_cols <- c("COA", target_cols)
# Subset the data
df_subset <- df[, target_cols]
# Reshape to long format
df_long <- pivot_longer(df_subset,
cols = setdiff(names(df_subset), "COA"),
names_to = "Metric",
values_to = "Score")
# Extract Construct and LLM
df_long$Construct <- sub("([A-Z]+)\\d+", "\\1", df_long$Metric)
df_long$LLM_ID <- as.integer(sub("[A-Z]+(\\d+)", "\\1", df_long$Metric))
df_long$LLM <- factor(df_long$LLM_ID, levels = 1:4, labels = llm_labels)
# Filter out non-finite values
df_long_filtered <- df_long[is.finite(df_long$Score), ]
# Create the main plot with proper legend
p <- ggplot(df_long_filtered, aes(x = Score, y = Construct, fill = LLM, pattern = LLM)) +
geom_boxplot_pattern(
position = position_dodge(width = 0.75),
outlier.shape = 21,
outlier.fill = "black",
pattern_fill = "white",
pattern_colour = "black",
pattern_density = 0.5,
pattern_spacing = 0.04,
pattern_size = 0.12
) +
scale_fill_brewer(palette = "Pastel1") +
scale_pattern_manual(values = c(
"ChatGPT" = "none",
"Claude" = "stripe",
"Gemini" = "crosshatch",
"Copilot" = "weave"
)) +
scale_x_continuous(limits = c(-5, 5)) +
labs(
title = "Distributions of LLM Evaluations by Construct",
x = "Score", y = "Construct", fill = "LLM", pattern = "LLM"
) +
theme_minimal(base_size = 16) +
theme(
plot.title = element_text(hjust = 0.5, face = "bold"),
legend.position = "bottom",
aspect.ratio = 1.0,
strip.text = element_text(size = 14),
axis.text.y = element_text(size = 14),
axis.title.y = element_text(size = 16),
legend.key.size = unit(1.5, "cm"), # Make legend keys bigger to show patterns
legend.text = element_text(size = 12)
) +
guides(
fill = guide_legend(override.aes = list(pattern = c("none", "stripe", "crosshatch", "weave"))),
pattern = guide_legend(override.aes = list(fill = scales::brewer_pal(palette = "Pastel1")(4)))
)
# Save the plot with increased height (tripled from 5 to 15)
ggsave("llm_construct_distributions_taller.png", p, width = 20, height = 25, dpi = 300)
# Show the plot
print(p)
9 Correlation Matrix
# Load required packages
if (!require("corrplot")) install.packages("corrplot", dependencies = TRUE)## Loading required package: corrplot## corrplot 0.95 loadedif (!require("viridis")) install.packages("viridis", dependencies = TRUE)
library(corrplot)
library(viridis)
ibm_palette <- c("#648FFF", # blue
"#785EF0", # purple
"#DC267F", # magenta
"#FE6100", # orange
"#FFB000", # yellow
"#00BFC4", # teal
"#009E73") # green
# Create interpolated IBM gradient
ibm_palette <- colorRampPalette(c("#648FFF", "#785EF0", "#DC267F", "#FE6100", "#FFB000", "#00BFC4", "#009E73"))(100)
# Read the data
data <- read.csv("finalscores1029.csv")
# Select only the rating variables (ICB1 through PV4)
rating_cols <- c("ICB1", "ICB2", "ICB3", "ICB4",
"T1", "T2", "T3", "T4",
"E1", "E2", "E3", "E4",
"S1", "S2", "S3", "S4",
"AF1", "AF2", "AF3", "AF4",
"PV1", "PV2", "PV3", "PV4")
rating_vars <- data[, rating_cols]
# Compute and round the correlation matrix
corr_matrix <- cor(rating_vars, , method="spearman",use = "pairwise.complete.obs")
corr_matrix_rounded <- round(corr_matrix, 2)
# Order variables logically by construct
ordered_vars <- rating_cols # Already ordered by construct
corr_matrix_ordered <- corr_matrix[ordered_vars, ordered_vars]
# Create color-blind friendly palette
viridis_colors <- viridis(100)
# Function to extract correlation matrix for a single construct
get_construct_correlations <- function(data, construct) {
cols <- grep(paste0("^", construct), names(data), value = TRUE)
cor(data[cols], use = "pairwise.complete.obs")
}
constructs <- c("ICB", "T", "E", "S", "AF", "PV")
# Main correlation matrix plot
corrplot(corr_matrix_ordered,
method = "circle",
type = "upper",
tl.col = "black",
tl.cex = 0.6, # smaller font for labels
tl.srt = 45,
cl.ratio = 0.2,
cl.align = "r",
addCoef.col=NULL, # remove correlation values in cells
col = ibm_palette,
diag = FALSE,
mar = c(1, 1, 3, 3),
title = "Correlation Matrix of Social Security Reform Ratings")
# 3x2 Construct panel plot
pdf("construct_correlation_plots.pdf", width = 10, height = 15)
par(mfrow = c(3, 2), mar = c(3, 3, 4, 2)) # Smaller margins
for (construct in constructs) {
corrplot(get_construct_correlations(rating_vars, construct),
method = "color",
type = "full",
tl.col = "black",
addCoef.col = "black",
number.cex = 1.2,
col = viridis_colors,
title = paste("Correlations for", construct))
}
dev.off()## png
## 2# Individual plots for each construct
for (construct in constructs) {
pdf(paste0(construct, "_correlation_plot.pdf"), width = 8, height = 7)
corrplot(get_construct_correlations(rating_vars, construct),
method = "color",
type = "full",
tl.col = "black",
addCoef.col = "black",
number.cex = .5,
col = viridis_colors,
title = paste("Correlations Among", construct, "Ratings"))
dev.off()
}
# Summary of construct-wise correlations
construct_consistency <- data.frame(
Construct = character(),
AvgCorrelation = numeric(),
MinCorrelation = numeric(),
MaxCorrelation = numeric(),
stringsAsFactors = FALSE
)
for (construct in constructs) {
corr_vals <- get_construct_correlations(rating_vars, construct)
vals <- corr_vals[lower.tri(corr_vals)]
construct_consistency <- rbind(construct_consistency, data.frame(
Construct = construct,
AvgCorrelation = mean(vals),
MinCorrelation = min(vals),
MaxCorrelation = max(vals)
))
}
print(construct_consistency)## Construct AvgCorrelation MinCorrelation MaxCorrelation
## 1 ICB 0.7083020 0.5622852 0.8381137
## 2 T 0.7563061 0.6592031 0.8924957
## 3 E 0.5372418 0.3862525 0.7181748
## 4 S 0.7488655 0.6036185 0.9145214
## 5 AF 0.4030040 0.1950817 0.5452120
## 6 PV 0.7851552 0.7202278 0.8520813write.csv(construct_consistency, "construct_consistency_summary.csv", row.names = FALSE)10 Cohen’s Kappa
# Load necessary package
library(psych)
# Define a function to compute kappa for all pairs in a group
compute_kappas <- function(df, var_prefix) {
cols <- grep(paste0("^", var_prefix), names(df), value = TRUE)
combinations <- combn(cols, 2, simplify = FALSE)
kappas <- lapply(combinations, function(pair) {
r1 <- df[[pair[1]]]
r2 <- df[[pair[2]]]
# Only include complete cases for fair comparison
complete_cases <- complete.cases(r1, r2)
kappa <- cohen.kappa(cbind(r1[complete_cases], r2[complete_cases]))
data.frame(
Rater1 = pair[1],
Rater2 = pair[2],
Kappa = kappa$kappa,
WeightedKappa = kappa$weighted.kappa
)
})
do.call(rbind, kappas)
}
# Run for ICB as an example
kappa_icb <- compute_kappas(rating_vars, "ICB")
kappa_trust <- compute_kappas(rating_vars, "T")
kappa_equity <- compute_kappas(rating_vars, "E")
kappa_s <- compute_kappas(rating_vars, "S")
kappa_af <- compute_kappas(rating_vars, "AF")
kappa_pv<- compute_kappas(rating_vars, "PV")
total=as.data.frame(rbind(kappa_icb, kappa_trust, kappa_equity, kappa_s, kappa_af, kappa_pv))
print(total)## Rater1 Rater2 Kappa WeightedKappa
## 1 ICB1 ICB2 0.21991557 0.82828943
## 2 ICB1 ICB3 0.21501309 0.60126745
## 3 ICB1 ICB4 0.38882103 0.76215104
## 4 ICB2 ICB3 0.06396291 0.63399505
## 5 ICB2 ICB4 0.10992079 0.68429607
## 6 ICB3 ICB4 0.17222671 0.50675070
## 7 T1 T2 0.19797368 0.77159027
## 8 T1 T3 0.19484968 0.64027697
## 9 T1 T4 0.20431757 0.67017466
## 10 T2 T3 0.18727106 0.76282315
## 11 T2 T4 0.29496728 0.87099068
## 12 T3 T4 0.13366170 0.56573554
## 13 E1 E2 0.08953881 0.66957258
## 14 E1 E3 0.01234568 0.44915726
## 15 E1 E4 0.17786012 0.37081294
## 16 E2 E3 0.10055424 0.53699969
## 17 E2 E4 0.12927951 0.41698273
## 18 E3 E4 0.04608777 0.33445900
## 19 S1 S2 0.15928034 0.86134062
## 20 S1 S3 0.21932390 0.78161562
## 21 S1 S4 0.10944944 0.50184894
## 22 S2 S3 0.13257919 0.82245719
## 23 S2 S4 0.29191950 0.61005750
## 24 S3 S4 0.02684180 0.49339104
## 25 AF1 AF2 0.09800363 0.36105237
## 26 AF1 AF3 0.12501481 0.33585746
## 27 AF1 AF4 0.24964522 0.36253283
## 28 AF2 AF3 0.02813688 0.08732773
## 29 AF2 AF4 -0.05891043 0.12324880
## 30 AF3 AF4 0.02210319 0.27772394
## 31 PV1 PV2 0.19400937 0.78949679
## 32 PV1 PV3 0.11131028 0.64216461
## 33 PV1 PV4 0.19923130 0.71677049
## 34 PV2 PV3 0.03455639 0.69529940
## 35 PV2 PV4 0.15577660 0.82064237
## 36 PV3 PV4 0.05151930 0.5458070711 Integer Goal Programming Approach to Policy Selection
11.1 Formulation
Formulation
11.2 Program
library(lpSolveAPI)
library(gtools)
library(dplyr)
set.seed(1234)
num_reps <- 100
df <- read.csv("finalscores1029.csv", strip.white = TRUE)
all_runs <- data.frame()
best_by_nmax <- tibble(
MaxCOAs = numeric(),
ObjVal = numeric()
)
num_coas <- 142
num_goals <- 24 # Only the first 24 goals are used for targets/deviations
ss_effect_col <- 25
total_vars <- num_coas + (2 * num_goals)
construct_names <- c("ICB", "T", "E", "S", "AF", "PV", "SS_Effect")
llm_names <- c("Inara", "Claude", "Gemini", "Copilot")
for (i in 1:num_reps) {
# Draw weights
construct_weights <- as.vector(rdirichlet(1, rep(1, 7)))
names(construct_weights) <- construct_names
llm_weights_list <- lapply(1:6, function(x) as.vector(rdirichlet(1, runif(4, 1, 5))))
flattened_llm_weights <- unlist(llm_weights_list)
expanded_construct_weights <- rep(construct_weights[1:6], each = 4)
final_weights <- expanded_construct_weights * flattened_llm_weights
weights <- c(final_weights, construct_weights["SS_Effect"])
names(weights) <- c(colnames(df[, 1:num_goals]), "SS_Effect")
max_num_coas <- sample(1:6, 1)
lambda <- runif(1, 0.2, 0.7)
# Setup LP
lprec <- make.lp(0, total_vars)
set.type(lprec, columns = 1:num_coas, type = "binary")
set.type(lprec, columns = (num_coas + 1):total_vars, type = "real")
targets <- rep(5, num_goals)
for (g in 1:num_goals) {
row <- numeric(total_vars)
row[1:num_coas] <- df[, g]
row[num_coas + g] <- 1
row[num_coas + num_goals + g] <- -1
add.constraint(lprec, row, "=", targets[g])
}
# Max COAs constraint
limit_row <- numeric(total_vars)
limit_row[1:140] <- 1
limit_row[141:142] <- 5
add.constraint(lprec, limit_row, "<=", max_num_coas)
# Privatization exclusivity
priv_row <- numeric(total_vars)
priv_row[141:142] <- 1
add.constraint(lprec, priv_row, "<=", 1)
# SS_Effect constraint
ss_effect_row <- numeric(total_vars)
ss_effect_row[1:num_coas] <- df[, ss_effect_col]
add.constraint(lprec, ss_effect_row, ">=", 3.5)
# Objective function
goal_matrix <- as.matrix(df[, 1:num_goals]) %*% diag(weights[1:num_goals])
obj <- rowSums(goal_matrix)
full_obj <- numeric(total_vars)
full_obj[1:num_coas] <- obj
full_obj[(num_coas + 1):(num_coas + num_goals)] <- -lambda
set.objfn(lprec, full_obj)
lp.control(lprec, sense = "max")
# Solve
status <- solve(lprec)
sol <- get.variables(lprec)
selected_indices <- which(sol[1:num_coas] == 1)
if (status == 0 && length(selected_indices) > 0) {
selected_COAs <- df[selected_indices, ]
selected_COAs$COA_ID <- as.integer(rownames(df)[selected_indices])
selected_COAs$WeightedScore <- obj[selected_indices]
selected_COAs$ObjVal <- get.objective(lprec)
selected_COAs$Run <- i
selected_COAs$Lambda <- lambda
selected_COAs$MaxCOAs <- max_num_coas
# Add construct weights and LLM contributions
for (j in seq_along(weights)) {
selected_COAs[[paste0("W_", names(weights)[j])]] <- weights[j]
}
llm_labels <- rep(llm_names, times = 6)
llm_contributions <- tapply(final_weights, llm_labels, sum)
llm_contributions <- llm_contributions / sum(final_weights)
for (llm in names(llm_contributions)) {
selected_COAs[[paste0("LLMWeight_", llm)]] <- llm_contributions[llm]
}
# Save all results
all_runs <- bind_rows(all_runs, selected_COAs)
# Save best result per Nmax
current_best <- best_by_nmax %>% filter(MaxCOAs == max_num_coas)
if (nrow(current_best) == 0 || selected_COAs$ObjVal[1] > max(current_best$ObjVal, na.rm = TRUE)) {
best_by_nmax <- best_by_nmax %>% filter(MaxCOAs != max_num_coas)
best_by_nmax <- bind_rows(best_by_nmax, selected_COAs)
}
} else {
cat(sprintf("Run %d infeasible or error\n", i))
}
}
# Output summaries
if (nrow(all_runs) > 0) {
summary_output <- all_runs %>%
group_by(Run) %>%
summarise(
`Objective Value` = first(ObjVal),
`Max COAs` = first(MaxCOAs),
Lambda = first(Lambda),
`COAs Selected` = paste(COA_ID, collapse = ", "),
`Types Selected` = paste(unique(Type), collapse = ", "),
`Weighted Scores` = paste(round(WeightedScore, 2), collapse = ", ")
) %>%
arrange(desc(`Objective Value`))
print(summary_output)
llm_summary <- all_runs %>%
dplyr::select(starts_with("LLMWeight_")) %>%
summarise(across(everything(), mean, na.rm = TRUE))
cat("\nAverage LLM Contributions Across Runs:\n")
print(round(llm_summary, 4))
}## # A tibble: 100 × 7
## Run `Objective Value` `Max COAs` Lambda `COAs Selected` `Types Selected`
## <int> <dbl> <int> <dbl> <chr> <chr>
## 1 14 7.37 6 0.460 29, 31, 32, 36, 9… BENEFITS, TAX
## 2 91 6.62 6 0.510 31, 32, 44, 78, 9… BENEFITS, FAMIL…
## 3 50 5.89 6 0.266 31, 32, 78, 83, 9… BENEFITS, FAMIL…
## 4 100 5.63 5 0.276 31, 32, 78, 91, 92 BENEFITS, FAMIL…
## 5 61 5.50 5 0.226 31, 32, 78, 91, 92 BENEFITS, FAMIL…
## 6 5 5.07 6 0.540 31, 32, 78, 83, 9… BENEFITS, FAMIL…
## 7 11 5.06 6 0.617 31, 32, 78, 83, 9… BENEFITS, FAMIL…
## 8 16 4.38 6 0.470 31, 32, 78, 83, 9… BENEFITS, FAMIL…
## 9 34 3.78 5 0.350 31, 32, 78, 91, 92 BENEFITS, FAMIL…
## 10 88 3.75 5 0.385 31, 32, 78, 90, 91 BENEFITS, FAMIL…
## # ℹ 90 more rows
## # ℹ 1 more variable: `Weighted Scores` <chr>## Warning: There was 1 warning in `summarise()`.
## ℹ In argument: `across(everything(), mean, na.rm = TRUE)`.
## Caused by warning:
## ! The `...` argument of `across()` is deprecated as of dplyr 1.1.0.
## Supply arguments directly to `.fns` through an anonymous function instead.
##
## # Previously
## across(a:b, mean, na.rm = TRUE)
##
## # Now
## across(a:b, \(x) mean(x, na.rm = TRUE))##
## Average LLM Contributions Across Runs:
## LLMWeight_Claude LLMWeight_Copilot LLMWeight_Gemini LLMWeight_Inara
## 1 0.2407 0.2547 0.2597 0.245# Save to files
write.csv(all_runs, "all_runs.csv", row.names = FALSE)
write.csv(best_by_nmax, "best_by_nmax.csv", row.names = FALSE)
write.csv(summary_output, "summary.csv", row.names = FALSE)
print(all_runs)## ICB1 ICB2 ICB3 ICB4 T1 T2 T3 T4 E1 E2 E3 E4 S1 S2 S3 S4 AF1 AF2 AF3 AF4 PV1
## 1 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 2 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 3 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 4 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 5 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 6 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 7 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 8 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 9 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 10 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 11 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 12 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 13 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 14 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 15 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 16 2 2 1 3 2 2 1 2 3 2 1 1 -1 -1 0 2 1 3 0 1 2
## 17 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 18 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 19 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 20 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 21 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 22 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 23 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 24 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 25 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 26 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 27 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 28 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 29 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 30 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 31 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 32 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 33 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 34 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 35 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 36 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 37 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 38 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 39 2 2 1 3 2 2 1 2 3 2 1 1 -1 -1 0 2 1 3 0 1 2
## 40 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 41 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 42 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 43 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 44 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 45 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 46 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 47 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 48 2 2 1 2 2 2 1 3 3 4 2 3 -1 -1 -1 -1 2 2 2 3 2
## 49 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 50 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 51 2 2 1 2 2 2 1 3 3 4 2 3 -1 -1 -1 -1 2 3 2 3 2
## 52 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 53 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 54 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 55 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 56 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 57 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 58 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 59 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 60 2 2 1 3 2 2 1 2 3 2 1 1 -1 -1 0 2 1 3 0 1 2
## 61 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 62 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 63 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 64 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 65 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 66 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 67 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 68 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 69 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 70 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 71 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 72 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 73 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 74 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 75 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 76 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 77 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 78 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 79 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 80 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 81 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 82 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 83 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 84 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 85 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 86 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 87 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 88 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 89 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 90 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 91 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 92 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 93 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 94 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 95 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 96 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 97 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 98 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 99 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 100 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 101 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 102 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 103 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 104 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 105 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 106 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 107 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 108 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 109 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 110 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 111 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 112 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 113 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 114 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 115 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 116 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 117 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 118 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 119 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 120 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 121 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 122 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 123 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 124 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 125 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 126 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 127 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 128 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 129 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 130 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 131 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 132 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 133 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 134 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 135 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 136 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 137 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 138 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 139 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 140 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 141 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 142 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 143 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 144 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 145 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 146 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 147 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 148 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 149 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 150 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 151 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 152 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 153 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 154 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 155 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 156 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 157 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 158 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 159 2 2 1 3 2 2 1 2 3 2 1 1 -1 -1 0 2 1 3 0 1 2
## 160 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 161 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 162 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 163 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 164 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 165 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 166 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 167 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 168 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 169 2 2 1 3 2 2 1 2 3 2 1 1 -1 -1 0 2 1 3 0 1 2
## 170 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 171 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 172 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 173 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 174 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 175 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 176 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 177 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 178 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 179 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 180 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 181 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 182 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 183 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 184 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 185 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 186 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 187 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 188 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 189 2 2 1 3 2 2 1 2 3 2 1 1 -1 -1 0 2 1 3 0 1 2
## 190 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 191 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 192 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 193 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 194 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 195 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 196 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 197 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 198 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 199 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 200 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 201 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 202 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 203 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 204 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 205 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 206 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 207 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 208 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 209 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 210 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 211 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 212 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 213 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 214 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 215 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 216 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 217 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 218 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 219 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 220 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 221 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 222 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 223 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 224 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 225 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 226 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 227 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 228 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 229 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 230 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 231 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 232 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 233 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 234 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 235 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 236 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 237 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 238 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 239 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 240 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 241 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 242 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 243 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 244 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 245 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 246 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 247 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 248 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 249 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 250 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 251 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 252 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 253 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 254 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 255 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 256 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 257 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 258 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 259 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 260 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 261 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 262 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 263 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 264 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 265 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 266 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 267 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 268 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 269 2 2 1 3 2 2 1 2 3 2 1 1 -1 -1 0 2 1 3 0 1 2
## 270 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 271 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 272 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 273 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 274 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 275 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 276 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 277 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 278 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 279 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 280 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 281 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 282 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 283 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 284 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 285 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 286 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 287 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 288 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 289 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 290 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 291 -1 1 0 3 0 2 0 2 1 2 0 2 1 -1 0 -1 4 4 2 3 1
## 292 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 293 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 294 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 295 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 296 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 297 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 298 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 299 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 300 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 301 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 302 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 303 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 304 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 305 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 306 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 307 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## 308 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 309 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 310 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 311 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 312 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 313 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 314 2 2 1 3 2 2 1 2 3 2 1 1 -1 -1 0 2 1 3 0 1 2
## 315 0 -2 1 0 -3 -2 1 -3 -2 3 3 1 4 4 3 4 2 3 0 2 -3
## 316 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 317 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 318 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 319 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 320 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 321 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 322 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 323 0 -4 0 0 1 -2 0 -5 1 -1 2 1 2 4 3 4 1 4 0 1 0
## 324 3 3 1 3 3 3 1 3 3 4 2 3 0 -1 -1 -1 2 2 2 3 2
## 325 3 3 1 3 2 3 1 3 3 4 2 3 -1 -1 -1 -1 3 3 2 3 4
## 326 0 2 1 0 5 3 1 3 4 3 0 -2 0 -1 0 3 2 3 1 5 3
## 327 0 -2 1 0 -2 0 0 -2 2 2 3 1 2 4 3 4 3 3 0 4 1
## 328 -1 -1 1 2 0 0 0 -1 0 3 3 1 3 3 3 3 2 2 0 -1 -4
## PV2 PV3 PV4 SS_Effect Type COA COA_ID WeightedScore ObjVal Run
## 1 -4 -1 -3 4.13 TAX 85 85 0.55012194 -38.90482907 1
## 2 2 1 4 0.00 BENEFITS 31 31 1.42449999 1.77736164 2
## 3 3 1 4 -0.13 BENEFITS 32 32 1.51947754 1.77736164 2
## 4 3 1 3 -0.10 FAMILY 78 78 0.67063624 1.77736164 2
## 5 -3 -1 -3 2.55 TAX 90 90 1.21481405 1.77736164 2
## 6 -2 -1 -3 1.86 TAX 91 91 1.34404616 1.77736164 2
## 7 3 1 4 -0.13 BENEFITS 32 32 2.12246451 -42.75263803 3
## 8 -4 -1 -3 4.13 TAX 85 85 0.32297467 -42.75263803 3
## 9 2 1 4 0.00 BENEFITS 31 31 1.55607982 -5.88017106 4
## 10 3 1 4 -0.13 BENEFITS 32 32 1.79725769 -5.88017106 4
## 11 3 1 3 -0.10 FAMILY 78 78 1.66210562 -5.88017106 4
## 12 -4 -1 -3 4.13 TAX 85 85 0.17657855 -5.88017106 4
## 13 2 1 4 0.00 BENEFITS 31 31 2.17483823 5.07014224 5
## 14 3 1 4 -0.13 BENEFITS 32 32 2.73698559 5.07014224 5
## 15 3 1 3 -0.10 FAMILY 78 78 2.25459062 5.07014224 5
## 16 3 1 3 -0.03 FAMILY 83 83 1.90637202 5.07014224 5
## 17 -3 -1 -3 2.55 TAX 90 90 -0.91650141 5.07014224 5
## 18 -2 -1 -3 1.86 TAX 91 91 0.15650421 5.07014224 5
## 19 2 1 4 0.00 BENEFITS 31 31 2.18238215 -0.70253101 6
## 20 3 1 4 -0.13 BENEFITS 32 32 2.65255181 -0.70253101 6
## 21 3 1 3 -0.10 FAMILY 78 78 1.91977376 -0.70253101 6
## 22 -2 -1 -3 1.86 TAX 91 91 -0.07403096 -0.70253101 6
## 23 -2 -1 -2 2.37 TAX 92 92 -0.92472779 -0.70253101 6
## 24 3 1 4 -0.13 BENEFITS 32 32 2.18488734 -15.06662316 7
## 25 -4 -1 -3 4.13 TAX 85 85 0.08665500 -15.06662316 7
## 26 2 1 4 0.00 BENEFITS 31 31 1.90928545 -18.83196612 8
## 27 3 1 4 -0.13 BENEFITS 32 32 2.23561898 -18.83196612 8
## 28 -4 -1 -3 4.13 TAX 85 85 0.40303014 -18.83196612 8
## 29 2 1 4 0.00 BENEFITS 31 31 1.96146097 3.74115544 9
## 30 3 1 4 -0.13 BENEFITS 32 32 2.22467600 3.74115544 9
## 31 3 1 3 -0.10 FAMILY 78 78 1.78860413 3.74115544 9
## 32 -3 -1 -3 2.55 TAX 90 90 0.49877905 3.74115544 9
## 33 -2 -1 -3 1.86 TAX 91 91 0.93326015 3.74115544 9
## 34 3 1 4 -0.13 BENEFITS 32 32 2.29334393 -28.62214692 10
## 35 -4 -1 -3 4.13 TAX 85 85 -0.15374172 -28.62214692 10
## 36 2 1 4 0.00 BENEFITS 31 31 2.29955596 5.06359268 11
## 37 3 1 4 -0.13 BENEFITS 32 32 2.34989958 5.06359268 11
## 38 3 1 3 -0.10 FAMILY 78 78 1.53672059 5.06359268 11
## 39 3 1 3 -0.03 FAMILY 83 83 1.69133514 5.06359268 11
## 40 -3 -1 -3 2.55 TAX 90 90 0.18810711 5.06359268 11
## 41 -2 -1 -3 1.86 TAX 91 91 0.69992264 5.06359268 11
## 42 2 1 4 0.00 BENEFITS 31 31 1.09138863 2.13220189 12
## 43 3 1 4 -0.13 BENEFITS 32 32 0.96483666 2.13220189 12
## 44 3 1 3 -0.10 FAMILY 78 78 1.22492688 2.13220189 12
## 45 -2 -1 -3 1.86 TAX 91 91 1.31016889 2.13220189 12
## 46 -2 -1 -2 2.37 TAX 92 92 1.31254202 2.13220189 12
## 47 -4 -1 -3 4.13 TAX 85 85 -0.04012003 -61.42462383 13
## 48 3 1 3 -0.06 BENEFITS 29 29 2.50846622 7.37186679 14
## 49 2 1 4 0.00 BENEFITS 31 31 2.49999764 7.37186679 14
## 50 3 1 4 -0.13 BENEFITS 32 32 2.60240729 7.37186679 14
## 51 2 1 3 -0.07 BENEFITS 36 36 2.45406444 7.37186679 14
## 52 -3 -1 -3 2.55 TAX 90 90 1.09163425 7.37186679 14
## 53 -2 -1 -3 1.86 TAX 91 91 1.27738835 7.37186679 14
## 54 2 1 4 0.00 BENEFITS 31 31 1.12490599 -18.98464610 15
## 55 3 1 4 -0.13 BENEFITS 32 32 1.03469461 -18.98464610 15
## 56 -4 -1 -3 4.13 TAX 85 85 1.48869730 -18.98464610 15
## 57 2 1 4 0.00 BENEFITS 31 31 1.52214555 4.37694220 16
## 58 3 1 4 -0.13 BENEFITS 32 32 1.54756167 4.37694220 16
## 59 3 1 3 -0.10 FAMILY 78 78 1.57493295 4.37694220 16
## 60 3 1 3 -0.03 FAMILY 83 83 1.26677267 4.37694220 16
## 61 -3 -1 -3 2.55 TAX 90 90 0.30809449 4.37694220 16
## 62 -2 -1 -3 1.86 TAX 91 91 0.97935044 4.37694220 16
## 63 2 1 4 0.00 BENEFITS 31 31 0.98920975 -15.62891949 17
## 64 3 1 4 -0.13 BENEFITS 32 32 1.10539410 -15.62891949 17
## 65 -4 -1 -3 4.13 TAX 85 85 1.08791977 -15.62891949 17
## 66 3 1 4 -0.13 BENEFITS 32 32 1.20896080 -45.32028888 18
## 67 -4 -1 -3 4.13 TAX 85 85 -0.05140139 -45.32028888 18
## 68 3 1 4 -0.13 BENEFITS 32 32 2.46332172 -27.88737521 19
## 69 -4 -1 -3 4.13 TAX 85 85 -0.08095728 -27.88737521 19
## 70 2 1 4 0.00 BENEFITS 31 31 1.40558964 -0.54100124 20
## 71 3 1 4 -0.13 BENEFITS 32 32 1.49505093 -0.54100124 20
## 72 3 1 3 -0.10 FAMILY 78 78 1.39099543 -0.54100124 20
## 73 -4 -1 -3 4.13 TAX 85 85 0.18895059 -0.54100124 20
## 74 3 1 4 -0.13 BENEFITS 32 32 1.41410972 -15.17185355 21
## 75 -4 -1 -3 4.13 TAX 85 85 0.06249604 -15.17185355 21
## 76 -4 -1 -3 4.13 TAX 85 85 0.28345134 -71.88695854 22
## 77 2 1 4 0.00 BENEFITS 31 31 2.43089716 2.67263766 23
## 78 3 1 4 -0.13 BENEFITS 32 32 2.39780478 2.67263766 23
## 79 3 1 3 -0.10 FAMILY 78 78 2.20689313 2.67263766 23
## 80 -2 -1 -3 1.86 TAX 91 91 -0.17851399 2.67263766 23
## 81 -2 -1 -2 2.37 TAX 92 92 0.03330951 2.67263766 23
## 82 2 1 4 0.00 BENEFITS 31 31 2.25890778 -3.80559056 24
## 83 3 1 4 -0.13 BENEFITS 32 32 2.46545581 -3.80559056 24
## 84 3 1 3 -0.10 FAMILY 78 78 1.64522843 -3.80559056 24
## 85 -4 -1 -3 4.13 TAX 85 85 -0.25929404 -3.80559056 24
## 86 -4 -1 -3 4.13 TAX 85 85 0.52422661 -55.22231834 25
## 87 3 1 4 -0.13 BENEFITS 32 32 2.68519292 -24.30796763 26
## 88 -4 -1 -3 4.13 TAX 85 85 0.24070379 -24.30796763 26
## 89 3 1 4 -0.13 BENEFITS 32 32 1.83126492 -23.26054481 27
## 90 -4 -1 -3 4.13 TAX 85 85 -0.26141718 -23.26054481 27
## 91 2 1 4 0.00 BENEFITS 31 31 2.10303914 -8.11553356 28
## 92 3 1 4 -0.13 BENEFITS 32 32 2.09801838 -8.11553356 28
## 93 -4 -1 -3 4.13 TAX 85 85 -0.73175643 -8.11553356 28
## 94 2 1 4 0.00 BENEFITS 31 31 1.73634548 -1.72685058 29
## 95 3 1 4 -0.13 BENEFITS 32 32 1.78795655 -1.72685058 29
## 96 3 1 3 -0.10 FAMILY 78 78 1.61569092 -1.72685058 29
## 97 -4 -1 -3 4.13 TAX 85 85 -0.19181922 -1.72685058 29
## 98 2 1 4 0.00 BENEFITS 31 31 2.51905137 -5.98261711 30
## 99 3 1 4 -0.13 BENEFITS 32 32 2.58477197 -5.98261711 30
## 100 3 1 3 -0.10 FAMILY 78 78 2.29219322 -5.98261711 30
## 101 -4 -1 -3 4.13 TAX 85 85 0.13999241 -5.98261711 30
## 102 -4 -1 -3 4.13 TAX 85 85 0.03615743 -58.44307482 31
## 103 2 1 4 0.00 BENEFITS 31 31 2.21066028 -16.80842752 32
## 104 3 1 4 -0.13 BENEFITS 32 32 2.21214476 -16.80842752 32
## 105 -4 -1 -3 4.13 TAX 85 85 -0.30680973 -16.80842752 32
## 106 2 1 4 0.00 BENEFITS 31 31 1.41152473 -19.06566900 33
## 107 3 1 4 -0.13 BENEFITS 32 32 1.52928984 -19.06566900 33
## 108 -4 -1 -3 4.13 TAX 85 85 1.17482218 -19.06566900 33
## 109 2 1 4 0.00 BENEFITS 31 31 1.53842928 3.78240692 34
## 110 3 1 4 -0.13 BENEFITS 32 32 1.57863645 3.78240692 34
## 111 3 1 3 -0.10 FAMILY 78 78 1.65931796 3.78240692 34
## 112 -2 -1 -3 1.86 TAX 91 91 1.27295869 3.78240692 34
## 113 -2 -1 -2 2.37 TAX 92 92 1.23127914 3.78240692 34
## 114 2 1 4 0.00 BENEFITS 31 31 2.29144909 -3.61202218 35
## 115 3 1 4 -0.13 BENEFITS 32 32 2.39727507 -3.61202218 35
## 116 3 1 3 -0.10 FAMILY 78 78 2.09295169 -3.61202218 35
## 117 -4 -1 -3 4.13 TAX 85 85 0.34169235 -3.61202218 35
## 118 2 1 4 0.00 BENEFITS 31 31 1.53215073 0.02624026 36
## 119 3 1 4 -0.13 BENEFITS 32 32 1.63968682 0.02624026 36
## 120 3 1 3 -0.10 FAMILY 78 78 1.17029519 0.02624026 36
## 121 -2 -1 -3 1.86 TAX 91 91 0.51804551 0.02624026 36
## 122 -2 -1 -2 2.37 TAX 92 92 0.35353994 0.02624026 36
## 123 -4 -1 -3 4.13 TAX 85 85 0.03706438 -36.40756985 37
## 124 2 1 4 0.00 BENEFITS 31 31 0.85457304 -0.23304293 38
## 125 3 1 4 -0.13 BENEFITS 32 32 0.83378956 -0.23304293 38
## 126 3 1 3 -0.10 FAMILY 78 78 0.75608952 -0.23304293 38
## 127 -2 -1 -3 1.86 TAX 91 91 0.44608159 -0.23304293 38
## 128 -2 -1 -2 2.37 TAX 92 92 0.57639522 -0.23304293 38
## 129 -4 -1 -3 4.13 TAX 85 85 0.06208171 -42.99281110 39
## 130 2 1 4 0.00 BENEFITS 31 31 1.59390268 3.15083189 40
## 131 3 1 4 -0.13 BENEFITS 32 32 1.67862928 3.15083189 40
## 132 3 1 3 -0.10 FAMILY 78 78 1.17620086 3.15083189 40
## 133 -2 -1 -3 1.86 TAX 91 91 1.12295345 3.15083189 40
## 134 -2 -1 -2 2.37 TAX 92 92 0.90415808 3.15083189 40
## 135 2 1 4 0.00 BENEFITS 31 31 1.86789706 -8.37561123 41
## 136 3 1 4 -0.13 BENEFITS 32 32 2.10629649 -8.37561123 41
## 137 -4 -1 -3 4.13 TAX 85 85 0.07475027 -8.37561123 41
## 138 -4 -1 -3 4.13 TAX 85 85 -0.61408078 -62.72638899 42
## 139 3 1 4 -0.13 BENEFITS 32 32 2.29820480 -38.28061177 43
## 140 -4 -1 -3 4.13 TAX 85 85 1.05430874 -38.28061177 43
## 141 3 1 4 -0.13 BENEFITS 32 32 1.98170341 -35.56557351 44
## 142 -4 -1 -3 4.13 TAX 85 85 -0.42823289 -35.56557351 44
## 143 2 1 4 0.00 BENEFITS 31 31 0.78856476 -21.65736790 45
## 144 3 1 4 -0.13 BENEFITS 32 32 0.93464525 -21.65736790 45
## 145 -4 -1 -3 4.13 TAX 85 85 0.31832753 -21.65736790 45
## 146 -4 -1 -3 4.13 TAX 85 85 0.67497731 -61.14532403 46
## 147 2 1 4 0.00 BENEFITS 31 31 2.26908493 0.82048565 47
## 148 3 1 4 -0.13 BENEFITS 32 32 2.57968471 0.82048565 47
## 149 3 1 3 -0.10 FAMILY 78 78 2.23960310 0.82048565 47
## 150 -4 -1 -3 4.13 TAX 85 85 -1.01683722 0.82048565 47
## 151 2 1 4 0.00 BENEFITS 31 31 1.87016010 0.10635596 48
## 152 3 1 4 -0.13 BENEFITS 32 32 1.83318450 0.10635596 48
## 153 3 1 3 -0.10 FAMILY 78 78 1.33607571 0.10635596 48
## 154 -4 -1 -3 4.13 TAX 85 85 0.48983794 0.10635596 48
## 155 -4 -1 -3 4.13 TAX 85 85 0.42101610 -50.58768595 49
## 156 2 1 4 0.00 BENEFITS 31 31 1.90730099 5.88779456 50
## 157 3 1 4 -0.13 BENEFITS 32 32 1.96150139 5.88779456 50
## 158 3 1 3 -0.10 FAMILY 78 78 1.60318772 5.88779456 50
## 159 3 1 3 -0.03 FAMILY 83 83 1.62012923 5.88779456 50
## 160 -3 -1 -3 2.55 TAX 90 90 0.01778655 5.88779456 50
## 161 -2 -1 -3 1.86 TAX 91 91 0.37333372 5.88779456 50
## 162 3 1 4 -0.13 BENEFITS 32 32 1.14861855 -32.24534982 51
## 163 -4 -1 -3 4.13 TAX 85 85 0.99120062 -32.24534982 51
## 164 3 1 4 -0.13 BENEFITS 32 32 0.90296047 -40.81224823 52
## 165 -4 -1 -3 4.13 TAX 85 85 0.08789148 -40.81224823 52
## 166 2 1 4 0.00 BENEFITS 31 31 1.30693494 2.76565432 53
## 167 3 1 4 -0.13 BENEFITS 32 32 1.50797799 2.76565432 53
## 168 3 1 3 -0.10 FAMILY 78 78 1.54107924 2.76565432 53
## 169 3 1 3 -0.03 FAMILY 83 83 1.04830328 2.76565432 53
## 170 -3 -1 -3 2.55 TAX 90 90 0.29595325 2.76565432 53
## 171 -2 -1 -3 1.86 TAX 91 91 0.64228117 2.76565432 53
## 172 2 1 4 0.00 BENEFITS 31 31 1.32487505 -7.69406583 54
## 173 3 1 4 -0.13 BENEFITS 32 32 1.20961919 -7.69406583 54
## 174 -4 -1 -3 4.13 TAX 85 85 0.84997062 -7.69406583 54
## 175 2 1 4 0.00 BENEFITS 31 31 2.11323746 -18.50694927 55
## 176 3 1 4 -0.13 BENEFITS 32 32 2.15617898 -18.50694927 55
## 177 -4 -1 -3 4.13 TAX 85 85 -0.17155566 -18.50694927 55
## 178 3 1 4 -0.13 BENEFITS 32 32 1.98100575 -27.32848598 56
## 179 -4 -1 -3 4.13 TAX 85 85 -0.12458093 -27.32848598 56
## 180 3 1 4 -0.13 BENEFITS 32 32 1.91571881 -26.21304569 57
## 181 -4 -1 -3 4.13 TAX 85 85 -1.12051981 -26.21304569 57
## 182 3 1 4 -0.13 BENEFITS 32 32 2.40839247 -17.81033616 58
## 183 -4 -1 -3 4.13 TAX 85 85 0.11792107 -17.81033616 58
## 184 3 1 4 -0.13 BENEFITS 32 32 1.68194555 -18.74252280 59
## 185 -4 -1 -3 4.13 TAX 85 85 -0.13487428 -18.74252280 59
## 186 2 1 4 0.00 BENEFITS 31 31 2.32688555 3.48201436 60
## 187 3 1 4 -0.13 BENEFITS 32 32 2.27046965 3.48201436 60
## 188 3 1 3 -0.10 FAMILY 78 78 2.61309441 3.48201436 60
## 189 3 1 3 -0.03 FAMILY 83 83 1.64018884 3.48201436 60
## 190 -3 -1 -3 2.55 TAX 90 90 -1.16521670 3.48201436 60
## 191 -2 -1 -3 1.86 TAX 91 91 -0.45091181 3.48201436 60
## 192 2 1 4 0.00 BENEFITS 31 31 2.39073824 5.50258992 61
## 193 3 1 4 -0.13 BENEFITS 32 32 2.34607852 5.50258992 61
## 194 3 1 3 -0.10 FAMILY 78 78 1.51063193 5.50258992 61
## 195 -2 -1 -3 1.86 TAX 91 91 0.76771717 5.50258992 61
## 196 -2 -1 -2 2.37 TAX 92 92 0.74960828 5.50258992 61
## 197 3 1 4 -0.13 BENEFITS 32 32 1.61416675 -15.52616846 62
## 198 -4 -1 -3 4.13 TAX 85 85 0.14726615 -15.52616846 62
## 199 2 1 4 0.00 BENEFITS 31 31 1.62164189 -9.50139821 63
## 200 3 1 4 -0.13 BENEFITS 32 32 1.73599475 -9.50139821 63
## 201 3 1 3 -0.10 FAMILY 78 78 1.44177291 -9.50139821 63
## 202 -4 -1 -3 4.13 TAX 85 85 -0.06235437 -9.50139821 63
## 203 2 1 4 0.00 BENEFITS 31 31 2.40052271 -3.16815830 64
## 204 3 1 4 -0.13 BENEFITS 32 32 2.81295205 -3.16815830 64
## 205 3 1 3 -0.10 FAMILY 78 78 1.94420684 -3.16815830 64
## 206 -4 -1 -3 4.13 TAX 85 85 -0.25656684 -3.16815830 64
## 207 3 1 4 -0.13 BENEFITS 32 32 1.87540877 -34.52179108 65
## 208 -4 -1 -3 4.13 TAX 85 85 0.77445257 -34.52179108 65
## 209 -4 -1 -3 4.13 TAX 85 85 0.36984273 -42.34179818 66
## 210 2 1 4 0.00 BENEFITS 31 31 0.18310918 -9.76456688 67
## 211 3 1 4 -0.13 BENEFITS 32 32 0.09875195 -9.76456688 67
## 212 -4 -1 -3 4.13 TAX 85 85 1.91264974 -9.76456688 67
## 213 2 1 4 0.00 BENEFITS 31 31 1.23303563 -10.17702441 68
## 214 3 1 4 -0.13 BENEFITS 32 32 1.27256507 -10.17702441 68
## 215 3 1 3 -0.10 FAMILY 78 78 0.81645512 -10.17702441 68
## 216 -4 -1 -3 4.13 TAX 85 85 0.30205335 -10.17702441 68
## 217 2 1 4 0.00 BENEFITS 31 31 1.13801979 -12.60784504 69
## 218 3 1 4 -0.13 BENEFITS 32 32 1.42132416 -12.60784504 69
## 219 -4 -1 -3 4.13 TAX 85 85 0.22351019 -12.60784504 69
## 220 2 1 4 0.00 BENEFITS 31 31 1.64621648 3.21634788 70
## 221 3 1 4 -0.13 BENEFITS 32 32 1.78499365 3.21634788 70
## 222 3 1 3 -0.10 FAMILY 78 78 1.97894976 3.21634788 70
## 223 -3 -1 -3 2.55 TAX 90 90 0.57347920 3.21634788 70
## 224 -2 -1 -3 1.86 TAX 91 91 1.08931765 3.21634788 70
## 225 3 1 4 -0.13 BENEFITS 32 32 1.88187629 -26.10264092 71
## 226 -4 -1 -3 4.13 TAX 85 85 -0.81360686 -26.10264092 71
## 227 2 1 4 0.00 BENEFITS 31 31 0.37270587 -11.27061009 72
## 228 3 1 4 -0.13 BENEFITS 32 32 0.27214665 -11.27061009 72
## 229 3 1 3 -0.10 FAMILY 78 78 0.73262321 -11.27061009 72
## 230 -4 -1 -3 4.13 TAX 85 85 1.90418459 -11.27061009 72
## 231 2 1 4 0.00 BENEFITS 31 31 1.89680106 -1.84321433 73
## 232 3 1 4 -0.13 BENEFITS 32 32 1.99513326 -1.84321433 73
## 233 3 1 3 -0.10 FAMILY 78 78 1.19282711 -1.84321433 73
## 234 -4 -1 -3 4.13 TAX 85 85 0.27751561 -1.84321433 73
## 235 2 1 4 0.00 BENEFITS 31 31 1.64785487 -15.49423264 74
## 236 3 1 4 -0.13 BENEFITS 32 32 1.59615790 -15.49423264 74
## 237 -4 -1 -3 4.13 TAX 85 85 -0.52256331 -15.49423264 74
## 238 2 1 4 0.00 BENEFITS 31 31 2.07693971 -20.64474453 75
## 239 3 1 4 -0.13 BENEFITS 32 32 2.62922998 -20.64474453 75
## 240 -4 -1 -3 4.13 TAX 85 85 -0.79491252 -20.64474453 75
## 241 -4 -1 -3 4.13 TAX 85 85 0.85898951 -63.36439725 76
## 242 2 1 4 0.00 BENEFITS 31 31 1.94811344 -0.26950963 77
## 243 3 1 4 -0.13 BENEFITS 32 32 2.05020003 -0.26950963 77
## 244 3 1 3 -0.10 FAMILY 78 78 1.50570321 -0.26950963 77
## 245 -2 -1 -3 1.86 TAX 91 91 0.16699324 -0.26950963 77
## 246 -2 -1 -2 2.37 TAX 92 92 0.37575131 -0.26950963 77
## 247 2 1 4 0.00 BENEFITS 31 31 1.02808199 -6.14944572 78
## 248 3 1 4 -0.13 BENEFITS 32 32 0.93525563 -6.14944572 78
## 249 -4 -1 -3 4.13 TAX 85 85 0.81358064 -6.14944572 78
## 250 2 1 4 0.00 BENEFITS 31 31 1.63854918 -5.85215225 79
## 251 3 1 4 -0.13 BENEFITS 32 32 1.82775374 -5.85215225 79
## 252 3 1 3 -0.10 FAMILY 78 78 1.56200100 -5.85215225 79
## 253 -4 -1 -3 4.13 TAX 85 85 0.03138428 -5.85215225 79
## 254 -4 -1 -3 4.13 TAX 85 85 -0.57441945 -27.24777985 80
## 255 2 1 4 0.00 BENEFITS 31 31 1.16436946 3.51004811 81
## 256 3 1 4 -0.13 BENEFITS 32 32 1.33642538 3.51004811 81
## 257 3 1 3 -0.10 FAMILY 78 78 1.19940088 3.51004811 81
## 258 -3 -1 -3 2.55 TAX 90 90 1.15050512 3.51004811 81
## 259 -2 -1 -3 1.86 TAX 91 91 1.39327772 3.51004811 81
## 260 3 1 4 -0.13 BENEFITS 32 32 2.25937772 -37.62706444 82
## 261 -4 -1 -3 4.13 TAX 85 85 -0.44012627 -37.62706444 82
## 262 -4 -1 -3 4.13 TAX 85 85 -0.94699556 -59.15875922 83
## 263 2 1 4 0.00 BENEFITS 31 31 1.31491182 -17.79669456 84
## 264 3 1 4 -0.13 BENEFITS 32 32 1.29834909 -17.79669456 84
## 265 -4 -1 -3 4.13 TAX 85 85 1.27170976 -17.79669456 84
## 266 2 1 4 0.00 BENEFITS 31 31 1.81704003 3.00445917 85
## 267 3 1 4 -0.13 BENEFITS 32 32 1.73707978 3.00445917 85
## 268 3 1 3 -0.10 FAMILY 78 78 1.05164842 3.00445917 85
## 269 3 1 3 -0.03 FAMILY 83 83 1.32820149 3.00445917 85
## 270 -3 -1 -3 2.55 TAX 90 90 0.49493433 3.00445917 85
## 271 -2 -1 -3 1.86 TAX 91 91 0.71504963 3.00445917 85
## 272 3 1 4 -0.13 BENEFITS 32 32 2.15035646 -31.48106424 86
## 273 -4 -1 -3 4.13 TAX 85 85 -0.08219009 -31.48106424 86
## 274 2 1 4 0.00 BENEFITS 31 31 2.12969038 -13.62684259 87
## 275 3 1 4 -0.13 BENEFITS 32 32 2.23388577 -13.62684259 87
## 276 -4 -1 -3 4.13 TAX 85 85 -0.06642338 -13.62684259 87
## 277 2 1 4 0.00 BENEFITS 31 31 2.10947817 3.75144698 88
## 278 3 1 4 -0.13 BENEFITS 32 32 2.48082966 3.75144698 88
## 279 3 1 3 -0.10 FAMILY 78 78 1.68001739 3.75144698 88
## 280 -3 -1 -3 2.55 TAX 90 90 0.41258368 3.75144698 88
## 281 -2 -1 -3 1.86 TAX 91 91 0.91662539 3.75144698 88
## 282 2 1 4 0.00 BENEFITS 31 31 1.92005314 3.10277317 89
## 283 3 1 4 -0.13 BENEFITS 32 32 1.89516069 3.10277317 89
## 284 3 1 3 -0.10 FAMILY 78 78 2.11928784 3.10277317 89
## 285 -2 -1 -3 1.86 TAX 91 91 0.42557189 3.10277317 89
## 286 -2 -1 -2 2.37 TAX 92 92 0.63507100 3.10277317 89
## 287 3 1 4 -0.13 BENEFITS 32 32 2.01946946 -19.67046355 90
## 288 -4 -1 -3 4.13 TAX 85 85 -0.38378957 -19.67046355 90
## 289 2 1 4 0.00 BENEFITS 31 31 1.68983748 6.62065090 91
## 290 3 1 4 -0.13 BENEFITS 32 32 1.97266038 6.62065090 91
## 291 2 0 3 -0.16 BENEFITS 44 44 1.74858380 6.62065090 91
## 292 3 1 3 -0.10 FAMILY 78 78 2.01233049 6.62065090 91
## 293 -3 -1 -3 2.55 TAX 90 90 1.03273592 6.62065090 91
## 294 -2 -1 -3 1.86 TAX 91 91 1.73709120 6.62065090 91
## 295 2 1 4 0.00 BENEFITS 31 31 2.00981544 -13.87854098 92
## 296 3 1 4 -0.13 BENEFITS 32 32 2.12601687 -13.87854098 92
## 297 -4 -1 -3 4.13 TAX 85 85 -0.53558283 -13.87854098 92
## 298 2 1 4 0.00 BENEFITS 31 31 1.87750530 -5.44388173 93
## 299 3 1 4 -0.13 BENEFITS 32 32 1.99169871 -5.44388173 93
## 300 -4 -1 -3 4.13 TAX 85 85 -0.54740905 -5.44388173 93
## 301 3 1 4 -0.13 BENEFITS 32 32 2.36854758 -40.35720561 94
## 302 -4 -1 -3 4.13 TAX 85 85 -0.05048373 -40.35720561 94
## 303 2 1 4 0.00 BENEFITS 31 31 2.36377416 2.85005469 95
## 304 3 1 4 -0.13 BENEFITS 32 32 2.74349117 2.85005469 95
## 305 3 1 3 -0.10 FAMILY 78 78 2.10911200 2.85005469 95
## 306 -2 -1 -3 1.86 TAX 91 91 -0.15544928 2.85005469 95
## 307 -2 -1 -2 2.37 TAX 92 92 -1.02938366 2.85005469 95
## 308 2 1 4 0.00 BENEFITS 31 31 1.65814188 -13.85004050 96
## 309 3 1 4 -0.13 BENEFITS 32 32 1.69852752 -13.85004050 96
## 310 -4 -1 -3 4.13 TAX 85 85 0.39432674 -13.85004050 96
## 311 2 1 4 0.00 BENEFITS 31 31 1.80441151 2.08182334 97
## 312 3 1 4 -0.13 BENEFITS 32 32 2.22388306 2.08182334 97
## 313 3 1 3 -0.10 FAMILY 78 78 1.88729449 2.08182334 97
## 314 3 1 3 -0.03 FAMILY 83 83 1.65590044 2.08182334 97
## 315 -3 -1 -3 2.55 TAX 90 90 -1.22643652 2.08182334 97
## 316 -2 -1 -3 1.86 TAX 91 91 -0.41468469 2.08182334 97
## 317 2 1 4 0.00 BENEFITS 31 31 2.44507802 -13.74442718 98
## 318 3 1 4 -0.13 BENEFITS 32 32 2.59723961 -13.74442718 98
## 319 -4 -1 -3 4.13 TAX 85 85 0.38978099 -13.74442718 98
## 320 2 1 4 0.00 BENEFITS 31 31 2.10598428 1.07165899 99
## 321 3 1 4 -0.13 BENEFITS 32 32 2.32425905 1.07165899 99
## 322 3 1 3 -0.10 FAMILY 78 78 2.18714980 1.07165899 99
## 323 -4 -1 -3 4.13 TAX 85 85 -0.59406883 1.07165899 99
## 324 2 1 4 0.00 BENEFITS 31 31 1.84339995 5.62925948 100
## 325 3 1 4 -0.13 BENEFITS 32 32 2.31092813 5.62925948 100
## 326 3 1 3 -0.10 FAMILY 78 78 1.71738302 5.62925948 100
## 327 -2 -1 -3 1.86 TAX 91 91 1.65323282 5.62925948 100
## 328 -2 -1 -2 2.37 TAX 92 92 0.86181894 5.62925948 100
## Lambda MaxCOAs W_ICB1 W_ICB2 W_ICB3 W_ICB4
## 1 0.3401289 1 0.0001838299 9.883054e-05 0.0006584170 0.0016154701
## 2 0.4396112 5 0.0023617509 4.804821e-03 0.0028727801 0.0050118212
## 3 0.4396112 5 0.0023617509 4.804821e-03 0.0028727801 0.0050118212
## 4 0.4396112 5 0.0023617509 4.804821e-03 0.0028727801 0.0050118212
## 5 0.4396112 5 0.0023617509 4.804821e-03 0.0028727801 0.0050118212
## 6 0.4396112 5 0.0023617509 4.804821e-03 0.0028727801 0.0050118212
## 7 0.6646776 2 0.0329083400 1.030722e-01 0.1361908632 0.0374585568
## 8 0.6646776 2 0.0329083400 1.030722e-01 0.1361908632 0.0374585568
## 9 0.5032815 4 0.0108112406 7.827756e-03 0.0162246290 0.0019671941
## 10 0.5032815 4 0.0108112406 7.827756e-03 0.0162246290 0.0019671941
## 11 0.5032815 4 0.0108112406 7.827756e-03 0.0162246290 0.0019671941
## 12 0.5032815 4 0.0108112406 7.827756e-03 0.0162246290 0.0019671941
## 13 0.5404412 6 0.0133521547 4.375085e-02 0.0190739662 0.0516813116
## 14 0.5404412 6 0.0133521547 4.375085e-02 0.0190739662 0.0516813116
## 15 0.5404412 6 0.0133521547 4.375085e-02 0.0190739662 0.0516813116
## 16 0.5404412 6 0.0133521547 4.375085e-02 0.0190739662 0.0516813116
## 17 0.5404412 6 0.0133521547 4.375085e-02 0.0190739662 0.0516813116
## 18 0.5404412 6 0.0133521547 4.375085e-02 0.0190739662 0.0516813116
## 19 0.6458480 5 0.1126242676 3.526082e-02 0.0282412461 0.0188316394
## 20 0.6458480 5 0.1126242676 3.526082e-02 0.0282412461 0.0188316394
## 21 0.6458480 5 0.1126242676 3.526082e-02 0.0282412461 0.0188316394
## 22 0.6458480 5 0.1126242676 3.526082e-02 0.0282412461 0.0188316394
## 23 0.6458480 5 0.1126242676 3.526082e-02 0.0282412461 0.0188316394
## 24 0.2549730 2 0.0030232001 7.268384e-03 0.0001703448 0.0015684225
## 25 0.2549730 2 0.0030232001 7.268384e-03 0.0001703448 0.0015684225
## 26 0.6318892 3 0.0365576579 8.551602e-02 0.0749715177 0.0911836648
## 27 0.6318892 3 0.0365576579 8.551602e-02 0.0749715177 0.0911836648
## 28 0.6318892 3 0.0365576579 8.551602e-02 0.0749715177 0.0911836648
## 29 0.3665625 5 0.0159962092 6.384150e-03 0.0019855838 0.0165266520
## 30 0.3665625 5 0.0159962092 6.384150e-03 0.0019855838 0.0165266520
## 31 0.3665625 5 0.0159962092 6.384150e-03 0.0019855838 0.0165266520
## 32 0.3665625 5 0.0159962092 6.384150e-03 0.0019855838 0.0165266520
## 33 0.3665625 5 0.0159962092 6.384150e-03 0.0019855838 0.0165266520
## 34 0.4523787 2 0.0188110331 4.148177e-02 0.0009304104 0.0449855132
## 35 0.4523787 2 0.0188110331 4.148177e-02 0.0009304104 0.0449855132
## 36 0.6169914 6 0.0379840218 5.628629e-02 0.0422307723 0.0866714351
## 37 0.6169914 6 0.0379840218 5.628629e-02 0.0422307723 0.0866714351
## 38 0.6169914 6 0.0379840218 5.628629e-02 0.0422307723 0.0866714351
## 39 0.6169914 6 0.0379840218 5.628629e-02 0.0422307723 0.0866714351
## 40 0.6169914 6 0.0379840218 5.628629e-02 0.0422307723 0.0866714351
## 41 0.6169914 6 0.0379840218 5.628629e-02 0.0422307723 0.0866714351
## 42 0.3771661 5 0.0461090724 1.739698e-02 0.0361743525 0.0326282322
## 43 0.3771661 5 0.0461090724 1.739698e-02 0.0361743525 0.0326282322
## 44 0.3771661 5 0.0461090724 1.739698e-02 0.0361743525 0.0326282322
## 45 0.3771661 5 0.0461090724 1.739698e-02 0.0361743525 0.0326282322
## 46 0.3771661 5 0.0461090724 1.739698e-02 0.0361743525 0.0326282322
## 47 0.5291768 1 0.0123473564 1.390957e-02 0.0495386888 0.0510129582
## 48 0.4601901 6 0.0202932791 5.923099e-03 0.0198952298 0.0032856383
## 49 0.4601901 6 0.0202932791 5.923099e-03 0.0198952298 0.0032856383
## 50 0.4601901 6 0.0202932791 5.923099e-03 0.0198952298 0.0032856383
## 51 0.4601901 6 0.0202932791 5.923099e-03 0.0198952298 0.0032856383
## 52 0.4601901 6 0.0202932791 5.923099e-03 0.0198952298 0.0032856383
## 53 0.4601901 6 0.0202932791 5.923099e-03 0.0198952298 0.0032856383
## 54 0.6117012 3 0.0697573804 4.097972e-02 0.0107696786 0.0100336705
## 55 0.6117012 3 0.0697573804 4.097972e-02 0.0107696786 0.0100336705
## 56 0.6117012 3 0.0697573804 4.097972e-02 0.0107696786 0.0100336705
## 57 0.4703193 6 0.0039260902 4.428387e-03 0.0048714300 0.0089556534
## 58 0.4703193 6 0.0039260902 4.428387e-03 0.0048714300 0.0089556534
## 59 0.4703193 6 0.0039260902 4.428387e-03 0.0048714300 0.0089556534
## 60 0.4703193 6 0.0039260902 4.428387e-03 0.0048714300 0.0089556534
## 61 0.4703193 6 0.0039260902 4.428387e-03 0.0048714300 0.0089556534
## 62 0.4703193 6 0.0039260902 4.428387e-03 0.0048714300 0.0089556534
## 63 0.5084174 3 0.0169102177 6.164914e-03 0.0130693077 0.0056782993
## 64 0.5084174 3 0.0169102177 6.164914e-03 0.0130693077 0.0056782993
## 65 0.5084174 3 0.0169102177 6.164914e-03 0.0130693077 0.0056782993
## 66 0.6834978 2 0.0003353111 1.286502e-03 0.0003846684 0.0004471789
## 67 0.6834978 2 0.0003353111 1.286502e-03 0.0003846684 0.0004471789
## 68 0.4451432 2 0.0394102284 2.629006e-02 0.0159810441 0.0036404115
## 69 0.4451432 2 0.0394102284 2.629006e-02 0.0159810441 0.0036404115
## 70 0.2282540 4 0.0070413824 1.556340e-02 0.0134364692 0.0177513124
## 71 0.2282540 4 0.0070413824 1.556340e-02 0.0134364692 0.0177513124
## 72 0.2282540 4 0.0070413824 1.556340e-02 0.0134364692 0.0177513124
## 73 0.2282540 4 0.0070413824 1.556340e-02 0.0134364692 0.0177513124
## 74 0.2448303 2 0.0045016593 2.303286e-02 0.0257592633 0.0058061626
## 75 0.2448303 2 0.0045016593 2.303286e-02 0.0257592633 0.0058061626
## 76 0.6221587 1 0.0352562193 2.428871e-02 0.0084199386 0.0045283487
## 77 0.4217753 5 0.0405540096 5.734813e-03 0.0094745055 0.0679823721
## 78 0.4217753 5 0.0405540096 5.734813e-03 0.0094745055 0.0679823721
## 79 0.4217753 5 0.0405540096 5.734813e-03 0.0094745055 0.0679823721
## 80 0.4217753 5 0.0405540096 5.734813e-03 0.0094745055 0.0679823721
## 81 0.4217753 5 0.0405540096 5.734813e-03 0.0094745055 0.0679823721
## 82 0.4507222 4 0.0366955403 7.985793e-02 0.0576355360 0.1212571428
## 83 0.4507222 4 0.0366955403 7.985793e-02 0.0576355360 0.1212571428
## 84 0.4507222 4 0.0366955403 7.985793e-02 0.0576355360 0.1212571428
## 85 0.4507222 4 0.0366955403 7.985793e-02 0.0576355360 0.1212571428
## 86 0.4805737 1 0.0529430141 4.449237e-02 0.0178349340 0.0477176816
## 87 0.4004980 2 0.0026514093 4.519869e-03 0.0013641120 0.0086985170
## 88 0.4004980 2 0.0026514093 4.519869e-03 0.0013641120 0.0086985170
## 89 0.3651528 2 0.0081216094 5.176442e-02 0.0089323017 0.0195962877
## 90 0.3651528 2 0.0081216094 5.176442e-02 0.0089323017 0.0195962877
## 91 0.3131036 3 0.0551266921 1.975941e-02 0.0028989693 0.0541575186
## 92 0.3131036 3 0.0551266921 1.975941e-02 0.0028989693 0.0541575186
## 93 0.3131036 3 0.0551266921 1.975941e-02 0.0028989693 0.0541575186
## 94 0.3034102 4 0.0644321672 1.692025e-01 0.0983674854 0.0273956480
## 95 0.3034102 4 0.0644321672 1.692025e-01 0.0983674854 0.0273956480
## 96 0.3034102 4 0.0644321672 1.692025e-01 0.0983674854 0.0273956480
## 97 0.3034102 4 0.0644321672 1.692025e-01 0.0983674854 0.0273956480
## 98 0.6144830 4 0.0013378236 2.782961e-02 0.0086522197 0.0256138393
## 99 0.6144830 4 0.0013378236 2.782961e-02 0.0086522197 0.0256138393
## 100 0.6144830 4 0.0013378236 2.782961e-02 0.0086522197 0.0256138393
## 101 0.6144830 4 0.0013378236 2.782961e-02 0.0086522197 0.0256138393
## 102 0.5041313 1 0.0117102981 1.943850e-02 0.0304809648 0.0238723817
## 103 0.5655249 3 0.0018354446 3.881888e-03 0.0009789519 0.0020682024
## 104 0.5655249 3 0.0018354446 3.881888e-03 0.0009789519 0.0020682024
## 105 0.5655249 3 0.0018354446 3.881888e-03 0.0009789519 0.0020682024
## 106 0.6265218 3 0.0146765929 1.320089e-02 0.0050406703 0.0106373518
## 107 0.6265218 3 0.0146765929 1.320089e-02 0.0050406703 0.0106373518
## 108 0.6265218 3 0.0146765929 1.320089e-02 0.0050406703 0.0106373518
## 109 0.3498215 5 0.0225812589 7.828021e-02 0.0807167348 0.1726258971
## 110 0.3498215 5 0.0225812589 7.828021e-02 0.0807167348 0.1726258971
## 111 0.3498215 5 0.0225812589 7.828021e-02 0.0807167348 0.1726258971
## 112 0.3498215 5 0.0225812589 7.828021e-02 0.0807167348 0.1726258971
## 113 0.3498215 5 0.0225812589 7.828021e-02 0.0807167348 0.1726258971
## 114 0.4879723 4 0.0177239188 5.260715e-02 0.0038315556 0.0288530104
## 115 0.4879723 4 0.0177239188 5.260715e-02 0.0038315556 0.0288530104
## 116 0.4879723 4 0.0177239188 5.260715e-02 0.0038315556 0.0288530104
## 117 0.4879723 4 0.0177239188 5.260715e-02 0.0038315556 0.0288530104
## 118 0.5187478 5 0.0493399808 1.159282e-02 0.1985197605 0.1080518717
## 119 0.5187478 5 0.0493399808 1.159282e-02 0.1985197605 0.1080518717
## 120 0.5187478 5 0.0493399808 1.159282e-02 0.1985197605 0.1080518717
## 121 0.5187478 5 0.0493399808 1.159282e-02 0.1985197605 0.1080518717
## 122 0.5187478 5 0.0493399808 1.159282e-02 0.1985197605 0.1080518717
## 123 0.3141779 1 0.0020147376 2.362725e-02 0.0070856578 0.0134499268
## 124 0.3699972 5 0.0498559992 4.304364e-02 0.0624977808 0.0806164595
## 125 0.3699972 5 0.0498559992 4.304364e-02 0.0624977808 0.0806164595
## 126 0.3699972 5 0.0498559992 4.304364e-02 0.0624977808 0.0806164595
## 127 0.3699972 5 0.0498559992 4.304364e-02 0.0624977808 0.0806164595
## 128 0.3699972 5 0.0498559992 4.304364e-02 0.0624977808 0.0806164595
## 129 0.3711629 1 0.0855586613 1.516438e-02 0.0259910851 0.0318429601
## 130 0.3325012 5 0.0029091976 2.661546e-03 0.0005859359 0.0005145686
## 131 0.3325012 5 0.0029091976 2.661546e-03 0.0005859359 0.0005145686
## 132 0.3325012 5 0.0029091976 2.661546e-03 0.0005859359 0.0005145686
## 133 0.3325012 5 0.0029091976 2.661546e-03 0.0005859359 0.0005145686
## 134 0.3325012 5 0.0029091976 2.661546e-03 0.0005859359 0.0005145686
## 135 0.3357988 3 0.0244663391 2.117738e-02 0.0100418530 0.0278642276
## 136 0.3357988 3 0.0244663391 2.117738e-02 0.0100418530 0.0278642276
## 137 0.3357988 3 0.0244663391 2.117738e-02 0.0100418530 0.0278642276
## 138 0.5354509 1 0.0023322196 2.601442e-02 0.0166497358 0.0388998345
## 139 0.6122518 2 0.0015833120 4.051343e-03 0.0023352111 0.0012105138
## 140 0.6122518 2 0.0015833120 4.051343e-03 0.0023352111 0.0012105138
## 141 0.5458683 2 0.0240732533 6.119764e-02 0.0096680189 0.0072326546
## 142 0.5458683 2 0.0240732533 6.119764e-02 0.0096680189 0.0072326546
## 143 0.6405110 3 0.0107412760 5.942964e-04 0.0030080155 0.0038880232
## 144 0.6405110 3 0.0107412760 5.942964e-04 0.0030080155 0.0038880232
## 145 0.6405110 3 0.0107412760 5.942964e-04 0.0030080155 0.0038880232
## 146 0.5329336 1 0.0821313667 3.332758e-02 0.0483955567 0.1146024120
## 147 0.2386841 4 0.0112323333 4.669456e-02 0.0070292563 0.0254808912
## 148 0.2386841 4 0.0112323333 4.669456e-02 0.0070292563 0.0254808912
## 149 0.2386841 4 0.0112323333 4.669456e-02 0.0070292563 0.0254808912
## 150 0.2386841 4 0.0112323333 4.669456e-02 0.0070292563 0.0254808912
## 151 0.2464956 4 0.0702459285 6.170310e-02 0.0463896512 0.1152270285
## 152 0.2464956 4 0.0702459285 6.170310e-02 0.0463896512 0.1152270285
## 153 0.2464956 4 0.0702459285 6.170310e-02 0.0463896512 0.1152270285
## 154 0.2464956 4 0.0702459285 6.170310e-02 0.0463896512 0.1152270285
## 155 0.4397302 1 0.0180249481 4.032243e-02 0.0043752757 0.0204715243
## 156 0.2659075 6 0.0615578468 1.363130e-01 0.0589309329 0.1308353615
## 157 0.2659075 6 0.0615578468 1.363130e-01 0.0589309329 0.1308353615
## 158 0.2659075 6 0.0615578468 1.363130e-01 0.0589309329 0.1308353615
## 159 0.2659075 6 0.0615578468 1.363130e-01 0.0589309329 0.1308353615
## 160 0.2659075 6 0.0615578468 1.363130e-01 0.0589309329 0.1308353615
## 161 0.2659075 6 0.0615578468 1.363130e-01 0.0589309329 0.1308353615
## 162 0.5056642 2 0.0329449075 3.700275e-02 0.0401867643 0.0346988377
## 163 0.5056642 2 0.0329449075 3.700275e-02 0.0401867643 0.0346988377
## 164 0.6147515 2 0.0220842384 1.672382e-02 0.0578699413 0.0403121727
## 165 0.6147515 2 0.0220842384 1.672382e-02 0.0578699413 0.0403121727
## 166 0.5961459 6 0.0055652002 2.112972e-02 0.0119166201 0.0155993833
## 167 0.5961459 6 0.0055652002 2.112972e-02 0.0119166201 0.0155993833
## 168 0.5961459 6 0.0055652002 2.112972e-02 0.0119166201 0.0155993833
## 169 0.5961459 6 0.0055652002 2.112972e-02 0.0119166201 0.0155993833
## 170 0.5961459 6 0.0055652002 2.112972e-02 0.0119166201 0.0155993833
## 171 0.5961459 6 0.0055652002 2.112972e-02 0.0119166201 0.0155993833
## 172 0.2994197 3 0.0374337815 5.497523e-03 0.0345255589 0.0401307305
## 173 0.2994197 3 0.0374337815 5.497523e-03 0.0345255589 0.0401307305
## 174 0.2994197 3 0.0374337815 5.497523e-03 0.0345255589 0.0401307305
## 175 0.6109408 3 0.0199543476 4.482619e-02 0.0959857770 0.2830108547
## 176 0.6109408 3 0.0199543476 4.482619e-02 0.0959857770 0.2830108547
## 177 0.6109408 3 0.0199543476 4.482619e-02 0.0959857770 0.2830108547
## 178 0.4291899 2 0.0227982595 8.159945e-03 0.0119830479 0.0225308867
## 179 0.4291899 2 0.0227982595 8.159945e-03 0.0119830479 0.0225308867
## 180 0.3971801 2 0.0106718921 3.530874e-02 0.0435970481 0.0449934202
## 181 0.3971801 2 0.0106718921 3.530874e-02 0.0435970481 0.0449934202
## 182 0.2990684 2 0.0050660087 6.660172e-02 0.0131103230 0.0710185082
## 183 0.2990684 2 0.0050660087 6.660172e-02 0.0131103230 0.0710185082
## 184 0.2983764 2 0.0381301015 1.556100e-01 0.0391872530 0.0522823848
## 185 0.2983764 2 0.0381301015 1.556100e-01 0.0391872530 0.0522823848
## 186 0.6254159 6 0.0114979080 7.766542e-02 0.0609092740 0.0448209825
## 187 0.6254159 6 0.0114979080 7.766542e-02 0.0609092740 0.0448209825
## 188 0.6254159 6 0.0114979080 7.766542e-02 0.0609092740 0.0448209825
## 189 0.6254159 6 0.0114979080 7.766542e-02 0.0609092740 0.0448209825
## 190 0.6254159 6 0.0114979080 7.766542e-02 0.0609092740 0.0448209825
## 191 0.6254159 6 0.0114979080 7.766542e-02 0.0609092740 0.0448209825
## 192 0.2262184 5 0.0550518538 8.238072e-02 0.0646593576 0.0386065314
## 193 0.2262184 5 0.0550518538 8.238072e-02 0.0646593576 0.0386065314
## 194 0.2262184 5 0.0550518538 8.238072e-02 0.0646593576 0.0386065314
## 195 0.2262184 5 0.0550518538 8.238072e-02 0.0646593576 0.0386065314
## 196 0.2262184 5 0.0550518538 8.238072e-02 0.0646593576 0.0386065314
## 197 0.2542294 2 0.0266534501 2.637782e-02 0.0614152742 0.0265479566
## 198 0.2542294 2 0.0266534501 2.637782e-02 0.0614152742 0.0265479566
## 199 0.6472024 4 0.0377259475 8.141959e-02 0.2924141166 0.0286613727
## 200 0.6472024 4 0.0377259475 8.141959e-02 0.2924141166 0.0286613727
## 201 0.6472024 4 0.0377259475 8.141959e-02 0.2924141166 0.0286613727
## 202 0.6472024 4 0.0377259475 8.141959e-02 0.2924141166 0.0286613727
## 203 0.4576942 4 0.0009833294 2.375982e-02 0.0005055121 0.0039418700
## 204 0.4576942 4 0.0009833294 2.375982e-02 0.0005055121 0.0039418700
## 205 0.4576942 4 0.0009833294 2.375982e-02 0.0005055121 0.0039418700
## 206 0.4576942 4 0.0009833294 2.375982e-02 0.0005055121 0.0039418700
## 207 0.5466419 2 0.0476571355 2.363452e-02 0.0283329460 0.0770138259
## 208 0.5466419 2 0.0476571355 2.363452e-02 0.0283329460 0.0770138259
## 209 0.3682038 1 0.0368734438 7.692654e-02 0.0621307989 0.0537595504
## 210 0.3232183 3 0.0146329893 1.586712e-02 0.0613132992 0.0471546094
## 211 0.3232183 3 0.0146329893 1.586712e-02 0.0613132992 0.0471546094
## 212 0.3232183 3 0.0146329893 1.586712e-02 0.0613132992 0.0471546094
## 213 0.6273243 4 0.0810831358 1.398281e-02 0.0993352501 0.0507074061
## 214 0.6273243 4 0.0810831358 1.398281e-02 0.0993352501 0.0507074061
## 215 0.6273243 4 0.0810831358 1.398281e-02 0.0993352501 0.0507074061
## 216 0.6273243 4 0.0810831358 1.398281e-02 0.0993352501 0.0507074061
## 217 0.4159648 3 0.0160935954 5.040460e-03 0.0041516901 0.0208421422
## 218 0.4159648 3 0.0160935954 5.040460e-03 0.0041516901 0.0208421422
## 219 0.4159648 3 0.0160935954 5.040460e-03 0.0041516901 0.0208421422
## 220 0.3856609 5 0.0260642864 1.875589e-02 0.0185252705 0.0040074709
## 221 0.3856609 5 0.0260642864 1.875589e-02 0.0185252705 0.0040074709
## 222 0.3856609 5 0.0260642864 1.875589e-02 0.0185252705 0.0040074709
## 223 0.3856609 5 0.0260642864 1.875589e-02 0.0185252705 0.0040074709
## 224 0.3856609 5 0.0260642864 1.875589e-02 0.0185252705 0.0040074709
## 225 0.3995722 2 0.0072569926 2.816133e-03 0.0007347589 0.0094415436
## 226 0.3995722 2 0.0072569926 2.816133e-03 0.0007347589 0.0094415436
## 227 0.6614668 4 0.0024866801 2.230748e-03 0.0002334788 0.0008804883
## 228 0.6614668 4 0.0024866801 2.230748e-03 0.0002334788 0.0008804883
## 229 0.6614668 4 0.0024866801 2.230748e-03 0.0002334788 0.0008804883
## 230 0.6614668 4 0.0024866801 2.230748e-03 0.0002334788 0.0008804883
## 231 0.3275223 4 0.1612968416 6.248670e-02 0.0323747278 0.1280088305
## 232 0.3275223 4 0.1612968416 6.248670e-02 0.0323747278 0.1280088305
## 233 0.3275223 4 0.1612968416 6.248670e-02 0.0323747278 0.1280088305
## 234 0.3275223 4 0.1612968416 6.248670e-02 0.0323747278 0.1280088305
## 235 0.4923157 3 0.0012610708 1.742157e-01 0.0490623984 0.1166824885
## 236 0.4923157 3 0.0012610708 1.742157e-01 0.0490623984 0.1166824885
## 237 0.4923157 3 0.0012610708 1.742157e-01 0.0490623984 0.1166824885
## 238 0.6636757 3 0.0381738949 2.376325e-02 0.0121623571 0.0071592110
## 239 0.6636757 3 0.0381738949 2.376325e-02 0.0121623571 0.0071592110
## 240 0.6636757 3 0.0381738949 2.376325e-02 0.0121623571 0.0071592110
## 241 0.5536499 1 0.0148688053 3.387540e-02 0.0353801998 0.0155235566
## 242 0.6316271 5 0.0046841724 9.005658e-02 0.1000233912 0.0631422285
## 243 0.6316271 5 0.0046841724 9.005658e-02 0.1000233912 0.0631422285
## 244 0.6316271 5 0.0046841724 9.005658e-02 0.1000233912 0.0631422285
## 245 0.6316271 5 0.0046841724 9.005658e-02 0.1000233912 0.0631422285
## 246 0.6316271 5 0.0046841724 9.005658e-02 0.1000233912 0.0631422285
## 247 0.2412531 3 0.0016404448 1.473482e-02 0.0091467469 0.0014389118
## 248 0.2412531 3 0.0016404448 1.473482e-02 0.0091467469 0.0014389118
## 249 0.2412531 3 0.0016404448 1.473482e-02 0.0091467469 0.0014389118
## 250 0.4959927 4 0.0309644470 8.437570e-02 0.0788220897 0.0108267284
## 251 0.4959927 4 0.0309644470 8.437570e-02 0.0788220897 0.0108267284
## 252 0.4959927 4 0.0309644470 8.437570e-02 0.0788220897 0.0108267284
## 253 0.4959927 4 0.0309644470 8.437570e-02 0.0788220897 0.0108267284
## 254 0.2299428 1 0.0020418793 2.081538e-03 0.0022051839 0.0086814516
## 255 0.2733930 5 0.0206471379 2.950590e-02 0.0172848972 0.0088651283
## 256 0.2733930 5 0.0206471379 2.950590e-02 0.0172848972 0.0088651283
## 257 0.2733930 5 0.0206471379 2.950590e-02 0.0172848972 0.0088651283
## 258 0.2733930 5 0.0206471379 2.950590e-02 0.0172848972 0.0088651283
## 259 0.2733930 5 0.0206471379 2.950590e-02 0.0172848972 0.0088651283
## 260 0.5800929 2 0.1799982233 1.936154e-01 0.0701481377 0.0816594161
## 261 0.5800929 2 0.1799982233 1.936154e-01 0.0701481377 0.0816594161
## 262 0.5018255 1 0.1032608082 9.792262e-02 0.0091547514 0.0211707584
## 263 0.5859910 3 0.0074278603 1.475833e-02 0.0251013428 0.0155282202
## 264 0.5859910 3 0.0074278603 1.475833e-02 0.0251013428 0.0155282202
## 265 0.5859910 3 0.0074278603 1.475833e-02 0.0251013428 0.0155282202
## 266 0.6899158 6 0.1303565497 1.096112e-01 0.0675815255 0.0900446334
## 267 0.6899158 6 0.1303565497 1.096112e-01 0.0675815255 0.0900446334
## 268 0.6899158 6 0.1303565497 1.096112e-01 0.0675815255 0.0900446334
## 269 0.6899158 6 0.1303565497 1.096112e-01 0.0675815255 0.0900446334
## 270 0.6899158 6 0.1303565497 1.096112e-01 0.0675815255 0.0900446334
## 271 0.6899158 6 0.1303565497 1.096112e-01 0.0675815255 0.0900446334
## 272 0.4933710 2 0.0254088688 3.741287e-02 0.0663058445 0.0353357203
## 273 0.4933710 2 0.0254088688 3.741287e-02 0.0663058445 0.0353357203
## 274 0.4844323 3 0.0507532866 6.176393e-02 0.0204874273 0.1291813431
## 275 0.4844323 3 0.0507532866 6.176393e-02 0.0204874273 0.1291813431
## 276 0.4844323 3 0.0507532866 6.176393e-02 0.0204874273 0.1291813431
## 277 0.3848087 5 0.0007297865 4.691957e-04 0.0011189161 0.0013575542
## 278 0.3848087 5 0.0007297865 4.691957e-04 0.0011189161 0.0013575542
## 279 0.3848087 5 0.0007297865 4.691957e-04 0.0011189161 0.0013575542
## 280 0.3848087 5 0.0007297865 4.691957e-04 0.0011189161 0.0013575542
## 281 0.3848087 5 0.0007297865 4.691957e-04 0.0011189161 0.0013575542
## 282 0.3892371 5 0.0360173684 8.677285e-03 0.0642268556 0.0577129672
## 283 0.3892371 5 0.0360173684 8.677285e-03 0.0642268556 0.0577129672
## 284 0.3892371 5 0.0360173684 8.677285e-03 0.0642268556 0.0577129672
## 285 0.3892371 5 0.0360173684 8.677285e-03 0.0642268556 0.0577129672
## 286 0.3892371 5 0.0360173684 8.677285e-03 0.0642268556 0.0577129672
## 287 0.3133256 2 0.0042500729 5.359088e-02 0.0309908126 0.0486426624
## 288 0.3133256 2 0.0042500729 5.359088e-02 0.0309908126 0.0486426624
## 289 0.5103698 6 0.0130876608 6.420881e-02 0.0281023776 0.0041623044
## 290 0.5103698 6 0.0130876608 6.420881e-02 0.0281023776 0.0041623044
## 291 0.5103698 6 0.0130876608 6.420881e-02 0.0281023776 0.0041623044
## 292 0.5103698 6 0.0130876608 6.420881e-02 0.0281023776 0.0041623044
## 293 0.5103698 6 0.0130876608 6.420881e-02 0.0281023776 0.0041623044
## 294 0.5103698 6 0.0130876608 6.420881e-02 0.0281023776 0.0041623044
## 295 0.4723997 3 0.0003825170 5.684642e-02 0.0633191905 0.0090034942
## 296 0.4723997 3 0.0003825170 5.684642e-02 0.0633191905 0.0090034942
## 297 0.4723997 3 0.0003825170 5.684642e-02 0.0633191905 0.0090034942
## 298 0.2369102 3 0.0683275062 8.837626e-02 0.0380780967 0.0197682052
## 299 0.2369102 3 0.0683275062 8.837626e-02 0.0380780967 0.0197682052
## 300 0.2369102 3 0.0683275062 8.837626e-02 0.0380780967 0.0197682052
## 301 0.6275775 2 0.0397364415 2.349145e-02 0.0273090405 0.0270031234
## 302 0.6275775 2 0.0397364415 2.349145e-02 0.0273090405 0.0270031234
## 303 0.3181490 5 0.0651867492 2.852917e-02 0.0131818195 0.0377804282
## 304 0.3181490 5 0.0651867492 2.852917e-02 0.0131818195 0.0377804282
## 305 0.3181490 5 0.0651867492 2.852917e-02 0.0131818195 0.0377804282
## 306 0.3181490 5 0.0651867492 2.852917e-02 0.0131818195 0.0377804282
## 307 0.3181490 5 0.0651867492 2.852917e-02 0.0131818195 0.0377804282
## 308 0.4757037 3 0.0951332309 1.518822e-02 0.0663424665 0.0026876478
## 309 0.4757037 3 0.0951332309 1.518822e-02 0.0663424665 0.0026876478
## 310 0.4757037 3 0.0951332309 1.518822e-02 0.0663424665 0.0026876478
## 311 0.6414242 6 0.0097727212 1.744939e-02 0.0302079380 0.0085411496
## 312 0.6414242 6 0.0097727212 1.744939e-02 0.0302079380 0.0085411496
## 313 0.6414242 6 0.0097727212 1.744939e-02 0.0302079380 0.0085411496
## 314 0.6414242 6 0.0097727212 1.744939e-02 0.0302079380 0.0085411496
## 315 0.6414242 6 0.0097727212 1.744939e-02 0.0302079380 0.0085411496
## 316 0.6414242 6 0.0097727212 1.744939e-02 0.0302079380 0.0085411496
## 317 0.5182845 3 0.0196632627 1.018709e-02 0.0192902030 0.0068917071
## 318 0.5182845 3 0.0196632627 1.018709e-02 0.0192902030 0.0068917071
## 319 0.5182845 3 0.0196632627 1.018709e-02 0.0192902030 0.0068917071
## 320 0.2250757 4 0.0230445792 3.008613e-02 0.0084943837 0.0282163312
## 321 0.2250757 4 0.0230445792 3.008613e-02 0.0084943837 0.0282163312
## 322 0.2250757 4 0.0230445792 3.008613e-02 0.0084943837 0.0282163312
## 323 0.2250757 4 0.0230445792 3.008613e-02 0.0084943837 0.0282163312
## 324 0.2757503 5 0.0164538584 1.608394e-02 0.0023216212 0.0340257348
## 325 0.2757503 5 0.0164538584 1.608394e-02 0.0023216212 0.0340257348
## 326 0.2757503 5 0.0164538584 1.608394e-02 0.0023216212 0.0340257348
## 327 0.2757503 5 0.0164538584 1.608394e-02 0.0023216212 0.0340257348
## 328 0.2757503 5 0.0164538584 1.608394e-02 0.0023216212 0.0340257348
## W_T1 W_T2 W_T3 W_T4 W_E1 W_E2
## 1 0.0829347944 0.0587632072 0.012458047 2.386577e-02 0.035324056 1.011492e-02
## 2 0.0021887070 0.0023820148 0.001698824 6.817475e-04 0.009969528 7.708648e-02
## 3 0.0021887070 0.0023820148 0.001698824 6.817475e-04 0.009969528 7.708648e-02
## 4 0.0021887070 0.0023820148 0.001698824 6.817475e-04 0.009969528 7.708648e-02
## 5 0.0021887070 0.0023820148 0.001698824 6.817475e-04 0.009969528 7.708648e-02
## 6 0.0021887070 0.0023820148 0.001698824 6.817475e-04 0.009969528 7.708648e-02
## 7 0.0040798296 0.0079520586 0.018976511 8.581507e-03 0.020607585 7.586557e-02
## 8 0.0040798296 0.0079520586 0.018976511 8.581507e-03 0.020607585 7.586557e-02
## 9 0.0076726277 0.0158855638 0.012362870 1.950940e-02 0.006512313 4.389882e-03
## 10 0.0076726277 0.0158855638 0.012362870 1.950940e-02 0.006512313 4.389882e-03
## 11 0.0076726277 0.0158855638 0.012362870 1.950940e-02 0.006512313 4.389882e-03
## 12 0.0076726277 0.0158855638 0.012362870 1.950940e-02 0.006512313 4.389882e-03
## 13 0.0172721667 0.0118959247 0.023895450 6.203828e-03 0.028214085 4.278555e-02
## 14 0.0172721667 0.0118959247 0.023895450 6.203828e-03 0.028214085 4.278555e-02
## 15 0.0172721667 0.0118959247 0.023895450 6.203828e-03 0.028214085 4.278555e-02
## 16 0.0172721667 0.0118959247 0.023895450 6.203828e-03 0.028214085 4.278555e-02
## 17 0.0172721667 0.0118959247 0.023895450 6.203828e-03 0.028214085 4.278555e-02
## 18 0.0172721667 0.0118959247 0.023895450 6.203828e-03 0.028214085 4.278555e-02
## 19 0.0343236498 0.0597383326 0.020321324 7.907545e-02 0.021449192 1.699150e-02
## 20 0.0343236498 0.0597383326 0.020321324 7.907545e-02 0.021449192 1.699150e-02
## 21 0.0343236498 0.0597383326 0.020321324 7.907545e-02 0.021449192 1.699150e-02
## 22 0.0343236498 0.0597383326 0.020321324 7.907545e-02 0.021449192 1.699150e-02
## 23 0.0343236498 0.0597383326 0.020321324 7.907545e-02 0.021449192 1.699150e-02
## 24 0.0360462465 0.0053442788 0.075234409 5.966873e-05 0.094505979 1.126200e-02
## 25 0.0360462465 0.0053442788 0.075234409 5.966873e-05 0.094505979 1.126200e-02
## 26 0.0140337643 0.0037517693 0.006493289 7.677122e-03 0.002759626 4.340607e-03
## 27 0.0140337643 0.0037517693 0.006493289 7.677122e-03 0.002759626 4.340607e-03
## 28 0.0140337643 0.0037517693 0.006493289 7.677122e-03 0.002759626 4.340607e-03
## 29 0.0005234777 0.0039353903 0.003717582 1.750476e-03 0.030522657 2.406493e-02
## 30 0.0005234777 0.0039353903 0.003717582 1.750476e-03 0.030522657 2.406493e-02
## 31 0.0005234777 0.0039353903 0.003717582 1.750476e-03 0.030522657 2.406493e-02
## 32 0.0005234777 0.0039353903 0.003717582 1.750476e-03 0.030522657 2.406493e-02
## 33 0.0005234777 0.0039353903 0.003717582 1.750476e-03 0.030522657 2.406493e-02
## 34 0.0368240813 0.0309398543 0.005932253 4.358162e-02 0.054594542 2.352817e-03
## 35 0.0368240813 0.0309398543 0.005932253 4.358162e-02 0.054594542 2.352817e-03
## 36 0.0013428904 0.0014618584 0.001338168 7.010304e-03 0.148643157 1.667539e-01
## 37 0.0013428904 0.0014618584 0.001338168 7.010304e-03 0.148643157 1.667539e-01
## 38 0.0013428904 0.0014618584 0.001338168 7.010304e-03 0.148643157 1.667539e-01
## 39 0.0013428904 0.0014618584 0.001338168 7.010304e-03 0.148643157 1.667539e-01
## 40 0.0013428904 0.0014618584 0.001338168 7.010304e-03 0.148643157 1.667539e-01
## 41 0.0013428904 0.0014618584 0.001338168 7.010304e-03 0.148643157 1.667539e-01
## 42 0.0809400624 0.0645115682 0.032269597 1.457513e-02 0.008460804 2.166304e-02
## 43 0.0809400624 0.0645115682 0.032269597 1.457513e-02 0.008460804 2.166304e-02
## 44 0.0809400624 0.0645115682 0.032269597 1.457513e-02 0.008460804 2.166304e-02
## 45 0.0809400624 0.0645115682 0.032269597 1.457513e-02 0.008460804 2.166304e-02
## 46 0.0809400624 0.0645115682 0.032269597 1.457513e-02 0.008460804 2.166304e-02
## 47 0.0913648760 0.0559904997 0.097467493 3.203180e-02 0.002628444 3.939376e-03
## 48 0.0039157804 0.0064603024 0.002819315 7.126189e-03 0.035503137 1.528196e-01
## 49 0.0039157804 0.0064603024 0.002819315 7.126189e-03 0.035503137 1.528196e-01
## 50 0.0039157804 0.0064603024 0.002819315 7.126189e-03 0.035503137 1.528196e-01
## 51 0.0039157804 0.0064603024 0.002819315 7.126189e-03 0.035503137 1.528196e-01
## 52 0.0039157804 0.0064603024 0.002819315 7.126189e-03 0.035503137 1.528196e-01
## 53 0.0039157804 0.0064603024 0.002819315 7.126189e-03 0.035503137 1.528196e-01
## 54 0.0625807072 0.0000567628 0.038893608 4.119933e-02 0.040620264 1.188386e-02
## 55 0.0625807072 0.0000567628 0.038893608 4.119933e-02 0.040620264 1.188386e-02
## 56 0.0625807072 0.0000567628 0.038893608 4.119933e-02 0.040620264 1.188386e-02
## 57 0.0677809893 0.0659438211 0.062542723 3.156408e-02 0.100048656 6.543025e-02
## 58 0.0677809893 0.0659438211 0.062542723 3.156408e-02 0.100048656 6.543025e-02
## 59 0.0677809893 0.0659438211 0.062542723 3.156408e-02 0.100048656 6.543025e-02
## 60 0.0677809893 0.0659438211 0.062542723 3.156408e-02 0.100048656 6.543025e-02
## 61 0.0677809893 0.0659438211 0.062542723 3.156408e-02 0.100048656 6.543025e-02
## 62 0.0677809893 0.0659438211 0.062542723 3.156408e-02 0.100048656 6.543025e-02
## 63 0.0251081292 0.0180559293 0.006490771 5.611906e-03 0.004506801 5.170183e-03
## 64 0.0251081292 0.0180559293 0.006490771 5.611906e-03 0.004506801 5.170183e-03
## 65 0.0251081292 0.0180559293 0.006490771 5.611906e-03 0.004506801 5.170183e-03
## 66 0.0041678765 0.0967280293 0.026015199 2.901351e-02 0.044732522 7.019681e-02
## 67 0.0041678765 0.0967280293 0.026015199 2.901351e-02 0.044732522 7.019681e-02
## 68 0.0130030922 0.0206190903 0.015708329 3.204769e-02 0.111793632 2.432738e-01
## 69 0.0130030922 0.0206190903 0.015708329 3.204769e-02 0.111793632 2.432738e-01
## 70 0.0155829868 0.0309579870 0.023020184 1.029896e-02 0.019884545 1.786482e-02
## 71 0.0155829868 0.0309579870 0.023020184 1.029896e-02 0.019884545 1.786482e-02
## 72 0.0155829868 0.0309579870 0.023020184 1.029896e-02 0.019884545 1.786482e-02
## 73 0.0155829868 0.0309579870 0.023020184 1.029896e-02 0.019884545 1.786482e-02
## 74 0.0108510472 0.0240019044 0.083571347 9.412877e-03 0.092798590 2.206460e-02
## 75 0.0108510472 0.0240019044 0.083571347 9.412877e-03 0.092798590 2.206460e-02
## 76 0.0918180399 0.0201622523 0.061219825 3.953867e-03 0.035871360 7.427506e-02
## 77 0.1164139517 0.0065465869 0.056395588 2.680378e-01 0.051033733 2.018044e-03
## 78 0.1164139517 0.0065465869 0.056395588 2.680378e-01 0.051033733 2.018044e-03
## 79 0.1164139517 0.0065465869 0.056395588 2.680378e-01 0.051033733 2.018044e-03
## 80 0.1164139517 0.0065465869 0.056395588 2.680378e-01 0.051033733 2.018044e-03
## 81 0.1164139517 0.0065465869 0.056395588 2.680378e-01 0.051033733 2.018044e-03
## 82 0.0112256018 0.0298083560 0.019788035 6.879741e-02 0.021395310 8.132016e-02
## 83 0.0112256018 0.0298083560 0.019788035 6.879741e-02 0.021395310 8.132016e-02
## 84 0.0112256018 0.0298083560 0.019788035 6.879741e-02 0.021395310 8.132016e-02
## 85 0.0112256018 0.0298083560 0.019788035 6.879741e-02 0.021395310 8.132016e-02
## 86 0.0030463987 0.0545450147 0.014726266 4.637817e-02 0.031008072 2.598278e-02
## 87 0.0059346442 0.0051619987 0.008297423 6.295311e-03 0.257678003 8.697561e-02
## 88 0.0059346442 0.0051619987 0.008297423 6.295311e-03 0.257678003 8.697561e-02
## 89 0.0236739357 0.1750369816 0.100710650 4.489227e-02 0.026337478 3.679504e-02
## 90 0.0236739357 0.1750369816 0.100710650 4.489227e-02 0.026337478 3.679504e-02
## 91 0.1123052570 0.1184297164 0.041733475 8.075641e-02 0.010119286 5.597944e-03
## 92 0.1123052570 0.1184297164 0.041733475 8.075641e-02 0.010119286 5.597944e-03
## 93 0.1123052570 0.1184297164 0.041733475 8.075641e-02 0.010119286 5.597944e-03
## 94 0.0353884834 0.0190731081 0.066166624 4.779077e-02 0.004522931 6.848060e-03
## 95 0.0353884834 0.0190731081 0.066166624 4.779077e-02 0.004522931 6.848060e-03
## 96 0.0353884834 0.0190731081 0.066166624 4.779077e-02 0.004522931 6.848060e-03
## 97 0.0353884834 0.0190731081 0.066166624 4.779077e-02 0.004522931 6.848060e-03
## 98 0.1017830572 0.0949125255 0.049927771 4.726691e-02 0.072753562 1.159404e-01
## 99 0.1017830572 0.0949125255 0.049927771 4.726691e-02 0.072753562 1.159404e-01
## 100 0.1017830572 0.0949125255 0.049927771 4.726691e-02 0.072753562 1.159404e-01
## 101 0.1017830572 0.0949125255 0.049927771 4.726691e-02 0.072753562 1.159404e-01
## 102 0.0263574151 0.0340765958 0.074345509 3.780148e-02 0.045840036 4.416925e-03
## 103 0.0145839050 0.0549462515 0.232414109 9.955188e-02 0.090249571 1.038668e-01
## 104 0.0145839050 0.0549462515 0.232414109 9.955188e-02 0.090249571 1.038668e-01
## 105 0.0145839050 0.0549462515 0.232414109 9.955188e-02 0.090249571 1.038668e-01
## 106 0.0275379797 0.0297303749 0.121603426 6.770847e-02 0.012228904 6.134384e-03
## 107 0.0275379797 0.0297303749 0.121603426 6.770847e-02 0.012228904 6.134384e-03
## 108 0.0275379797 0.0297303749 0.121603426 6.770847e-02 0.012228904 6.134384e-03
## 109 0.0197345525 0.0135432550 0.036785455 5.774854e-02 0.005831688 1.394580e-02
## 110 0.0197345525 0.0135432550 0.036785455 5.774854e-02 0.005831688 1.394580e-02
## 111 0.0197345525 0.0135432550 0.036785455 5.774854e-02 0.005831688 1.394580e-02
## 112 0.0197345525 0.0135432550 0.036785455 5.774854e-02 0.005831688 1.394580e-02
## 113 0.0197345525 0.0135432550 0.036785455 5.774854e-02 0.005831688 1.394580e-02
## 114 0.0637782565 0.0351832727 0.010429566 1.527300e-02 0.073911902 1.868696e-02
## 115 0.0637782565 0.0351832727 0.010429566 1.527300e-02 0.073911902 1.868696e-02
## 116 0.0637782565 0.0351832727 0.010429566 1.527300e-02 0.073911902 1.868696e-02
## 117 0.0637782565 0.0351832727 0.010429566 1.527300e-02 0.073911902 1.868696e-02
## 118 0.0139484133 0.0045121730 0.061198860 1.437702e-02 0.006779422 6.560678e-03
## 119 0.0139484133 0.0045121730 0.061198860 1.437702e-02 0.006779422 6.560678e-03
## 120 0.0139484133 0.0045121730 0.061198860 1.437702e-02 0.006779422 6.560678e-03
## 121 0.0139484133 0.0045121730 0.061198860 1.437702e-02 0.006779422 6.560678e-03
## 122 0.0139484133 0.0045121730 0.061198860 1.437702e-02 0.006779422 6.560678e-03
## 123 0.0567289347 0.0080769381 0.003888326 5.392911e-02 0.167944953 1.626135e-01
## 124 0.0333921419 0.0404028189 0.001623412 1.501084e-02 0.003199632 4.209695e-03
## 125 0.0333921419 0.0404028189 0.001623412 1.501084e-02 0.003199632 4.209695e-03
## 126 0.0333921419 0.0404028189 0.001623412 1.501084e-02 0.003199632 4.209695e-03
## 127 0.0333921419 0.0404028189 0.001623412 1.501084e-02 0.003199632 4.209695e-03
## 128 0.0333921419 0.0404028189 0.001623412 1.501084e-02 0.003199632 4.209695e-03
## 129 0.0574519248 0.0209104888 0.081597103 8.442559e-02 0.020232958 2.046533e-02
## 130 0.0091766816 0.0158762899 0.010887256 1.338971e-02 0.040436352 3.889847e-02
## 131 0.0091766816 0.0158762899 0.010887256 1.338971e-02 0.040436352 3.889847e-02
## 132 0.0091766816 0.0158762899 0.010887256 1.338971e-02 0.040436352 3.889847e-02
## 133 0.0091766816 0.0158762899 0.010887256 1.338971e-02 0.040436352 3.889847e-02
## 134 0.0091766816 0.0158762899 0.010887256 1.338971e-02 0.040436352 3.889847e-02
## 135 0.0174690924 0.0167959239 0.028196596 3.893758e-02 0.011427010 1.172303e-02
## 136 0.0174690924 0.0167959239 0.028196596 3.893758e-02 0.011427010 1.172303e-02
## 137 0.0174690924 0.0167959239 0.028196596 3.893758e-02 0.011427010 1.172303e-02
## 138 0.0120645288 0.1296550301 0.037196883 1.231201e-01 0.031711836 1.717877e-02
## 139 0.0497174105 0.0831893083 0.100599613 2.615460e-02 0.013290156 1.389059e-02
## 140 0.0497174105 0.0831893083 0.100599613 2.615460e-02 0.013290156 1.389059e-02
## 141 0.0837337637 0.0414723856 0.020975443 2.020669e-02 0.074581411 2.377582e-02
## 142 0.0837337637 0.0414723856 0.020975443 2.020669e-02 0.074581411 2.377582e-02
## 143 0.0131831624 0.0356511494 0.020436406 3.285280e-02 0.009433806 4.857883e-03
## 144 0.0131831624 0.0356511494 0.020436406 3.285280e-02 0.009433806 4.857883e-03
## 145 0.0131831624 0.0356511494 0.020436406 3.285280e-02 0.009433806 4.857883e-03
## 146 0.0880905610 0.0550901654 0.100494676 5.711581e-02 0.002807230 2.533012e-03
## 147 0.0443814577 0.0922043026 0.144390781 8.019937e-02 0.004116962 1.033936e-02
## 148 0.0443814577 0.0922043026 0.144390781 8.019937e-02 0.004116962 1.033936e-02
## 149 0.0443814577 0.0922043026 0.144390781 8.019937e-02 0.004116962 1.033936e-02
## 150 0.0443814577 0.0922043026 0.144390781 8.019937e-02 0.004116962 1.033936e-02
## 151 0.0453288927 0.0194591824 0.009716349 1.840005e-02 0.085288902 2.194918e-02
## 152 0.0453288927 0.0194591824 0.009716349 1.840005e-02 0.085288902 2.194918e-02
## 153 0.0453288927 0.0194591824 0.009716349 1.840005e-02 0.085288902 2.194918e-02
## 154 0.0453288927 0.0194591824 0.009716349 1.840005e-02 0.085288902 2.194918e-02
## 155 0.0883010508 0.0492123794 0.012853034 1.836216e-02 0.051366539 8.001357e-02
## 156 0.0387574559 0.0800909954 0.080700135 4.082416e-02 0.000543499 7.996184e-03
## 157 0.0387574559 0.0800909954 0.080700135 4.082416e-02 0.000543499 7.996184e-03
## 158 0.0387574559 0.0800909954 0.080700135 4.082416e-02 0.000543499 7.996184e-03
## 159 0.0387574559 0.0800909954 0.080700135 4.082416e-02 0.000543499 7.996184e-03
## 160 0.0387574559 0.0800909954 0.080700135 4.082416e-02 0.000543499 7.996184e-03
## 161 0.0387574559 0.0800909954 0.080700135 4.082416e-02 0.000543499 7.996184e-03
## 162 0.0052212549 0.0025122499 0.006484314 8.627715e-03 0.005502616 1.258160e-03
## 163 0.0052212549 0.0025122499 0.006484314 8.627715e-03 0.005502616 1.258160e-03
## 164 0.0007902179 0.0083538920 0.004612756 1.562998e-02 0.008910324 1.532047e-02
## 165 0.0007902179 0.0083538920 0.004612756 1.562998e-02 0.008910324 1.532047e-02
## 166 0.0066034625 0.0083217772 0.001113359 1.230307e-02 0.003336484 4.090262e-03
## 167 0.0066034625 0.0083217772 0.001113359 1.230307e-02 0.003336484 4.090262e-03
## 168 0.0066034625 0.0083217772 0.001113359 1.230307e-02 0.003336484 4.090262e-03
## 169 0.0066034625 0.0083217772 0.001113359 1.230307e-02 0.003336484 4.090262e-03
## 170 0.0066034625 0.0083217772 0.001113359 1.230307e-02 0.003336484 4.090262e-03
## 171 0.0066034625 0.0083217772 0.001113359 1.230307e-02 0.003336484 4.090262e-03
## 172 0.1235430062 0.1458212714 0.019838255 1.559268e-02 0.021992780 4.678030e-02
## 173 0.1235430062 0.1458212714 0.019838255 1.559268e-02 0.021992780 4.678030e-02
## 174 0.1235430062 0.1458212714 0.019838255 1.559268e-02 0.021992780 4.678030e-02
## 175 0.0082873982 0.0682686543 0.066343191 4.847861e-02 0.021013030 4.272111e-02
## 176 0.0082873982 0.0682686543 0.066343191 4.847861e-02 0.021013030 4.272111e-02
## 177 0.0082873982 0.0682686543 0.066343191 4.847861e-02 0.021013030 4.272111e-02
## 178 0.0133378121 0.0088929559 0.015796895 4.782251e-02 0.029259467 1.211582e-02
## 179 0.0133378121 0.0088929559 0.015796895 4.782251e-02 0.029259467 1.211582e-02
## 180 0.0396467091 0.0607775964 0.206481611 1.603643e-01 0.006724413 7.905064e-03
## 181 0.0396467091 0.0607775964 0.206481611 1.603643e-01 0.006724413 7.905064e-03
## 182 0.0817590774 0.0237134890 0.063171289 5.380235e-02 0.040390223 3.065439e-03
## 183 0.0817590774 0.0237134890 0.063171289 5.380235e-02 0.040390223 3.065439e-03
## 184 0.0200843183 0.0095945229 0.016996059 4.319726e-02 0.013357442 1.954445e-02
## 185 0.0200843183 0.0095945229 0.016996059 4.319726e-02 0.013357442 1.954445e-02
## 186 0.2208668344 0.0493067561 0.058254907 1.033147e-01 0.001284845 2.051042e-03
## 187 0.2208668344 0.0493067561 0.058254907 1.033147e-01 0.001284845 2.051042e-03
## 188 0.2208668344 0.0493067561 0.058254907 1.033147e-01 0.001284845 2.051042e-03
## 189 0.2208668344 0.0493067561 0.058254907 1.033147e-01 0.001284845 2.051042e-03
## 190 0.2208668344 0.0493067561 0.058254907 1.033147e-01 0.001284845 2.051042e-03
## 191 0.2208668344 0.0493067561 0.058254907 1.033147e-01 0.001284845 2.051042e-03
## 192 0.0583725707 0.0443527822 0.012065411 8.422960e-02 0.105707795 6.016240e-02
## 193 0.0583725707 0.0443527822 0.012065411 8.422960e-02 0.105707795 6.016240e-02
## 194 0.0583725707 0.0443527822 0.012065411 8.422960e-02 0.105707795 6.016240e-02
## 195 0.0583725707 0.0443527822 0.012065411 8.422960e-02 0.105707795 6.016240e-02
## 196 0.0583725707 0.0443527822 0.012065411 8.422960e-02 0.105707795 6.016240e-02
## 197 0.0201488952 0.0068336308 0.001367893 1.076136e-02 0.060806855 5.764037e-03
## 198 0.0201488952 0.0068336308 0.001367893 1.076136e-02 0.060806855 5.764037e-03
## 199 0.0185522485 0.0159218666 0.016778572 3.011087e-03 0.063461721 7.969093e-05
## 200 0.0185522485 0.0159218666 0.016778572 3.011087e-03 0.063461721 7.969093e-05
## 201 0.0185522485 0.0159218666 0.016778572 3.011087e-03 0.063461721 7.969093e-05
## 202 0.0185522485 0.0159218666 0.016778572 3.011087e-03 0.063461721 7.969093e-05
## 203 0.0072825188 0.0461737290 0.018682627 2.085850e-02 0.006423264 4.299990e-02
## 204 0.0072825188 0.0461737290 0.018682627 2.085850e-02 0.006423264 4.299990e-02
## 205 0.0072825188 0.0461737290 0.018682627 2.085850e-02 0.006423264 4.299990e-02
## 206 0.0072825188 0.0461737290 0.018682627 2.085850e-02 0.006423264 4.299990e-02
## 207 0.0023006211 0.0204219619 0.008984489 2.845831e-03 0.042463458 4.017863e-02
## 208 0.0023006211 0.0204219619 0.008984489 2.845831e-03 0.042463458 4.017863e-02
## 209 0.0026180813 0.0103817368 0.017316780 7.147194e-03 0.073136909 3.529952e-02
## 210 0.0056781065 0.0382771645 0.010925930 2.115990e-02 0.010780906 1.331566e-03
## 211 0.0056781065 0.0382771645 0.010925930 2.115990e-02 0.010780906 1.331566e-03
## 212 0.0056781065 0.0382771645 0.010925930 2.115990e-02 0.010780906 1.331566e-03
## 213 0.0095366931 0.0115593228 0.040696709 9.464103e-03 0.014278058 3.551804e-03
## 214 0.0095366931 0.0115593228 0.040696709 9.464103e-03 0.014278058 3.551804e-03
## 215 0.0095366931 0.0115593228 0.040696709 9.464103e-03 0.014278058 3.551804e-03
## 216 0.0095366931 0.0115593228 0.040696709 9.464103e-03 0.014278058 3.551804e-03
## 217 0.0043537671 0.0084085894 0.007529355 1.020895e-03 0.009910862 1.073994e-02
## 218 0.0043537671 0.0084085894 0.007529355 1.020895e-03 0.009910862 1.073994e-02
## 219 0.0043537671 0.0084085894 0.007529355 1.020895e-03 0.009910862 1.073994e-02
## 220 0.0013200774 0.0009623663 0.001873638 1.093575e-02 0.067686658 6.484729e-02
## 221 0.0013200774 0.0009623663 0.001873638 1.093575e-02 0.067686658 6.484729e-02
## 222 0.0013200774 0.0009623663 0.001873638 1.093575e-02 0.067686658 6.484729e-02
## 223 0.0013200774 0.0009623663 0.001873638 1.093575e-02 0.067686658 6.484729e-02
## 224 0.0013200774 0.0009623663 0.001873638 1.093575e-02 0.067686658 6.484729e-02
## 225 0.0280464012 0.0008078966 0.013898883 2.561586e-01 0.038152237 1.922930e-02
## 226 0.0280464012 0.0008078966 0.013898883 2.561586e-01 0.038152237 1.922930e-02
## 227 0.0104620505 0.0010533943 0.004797934 1.216811e-02 0.047084484 4.026721e-02
## 228 0.0104620505 0.0010533943 0.004797934 1.216811e-02 0.047084484 4.026721e-02
## 229 0.0104620505 0.0010533943 0.004797934 1.216811e-02 0.047084484 4.026721e-02
## 230 0.0104620505 0.0010533943 0.004797934 1.216811e-02 0.047084484 4.026721e-02
## 231 0.0187962308 0.0105034527 0.038355883 1.472583e-02 0.020056504 3.574741e-03
## 232 0.0187962308 0.0105034527 0.038355883 1.472583e-02 0.020056504 3.574741e-03
## 233 0.0187962308 0.0105034527 0.038355883 1.472583e-02 0.020056504 3.574741e-03
## 234 0.0187962308 0.0105034527 0.038355883 1.472583e-02 0.020056504 3.574741e-03
## 235 0.0919850304 0.0282910543 0.014376405 2.840333e-02 0.014565990 1.743678e-02
## 236 0.0919850304 0.0282910543 0.014376405 2.840333e-02 0.014565990 1.743678e-02
## 237 0.0919850304 0.0282910543 0.014376405 2.840333e-02 0.014565990 1.743678e-02
## 238 0.0294316040 0.0138578465 0.019545614 1.335833e-02 0.011342368 9.690994e-03
## 239 0.0294316040 0.0138578465 0.019545614 1.335833e-02 0.011342368 9.690994e-03
## 240 0.0294316040 0.0138578465 0.019545614 1.335833e-02 0.011342368 9.690994e-03
## 241 0.0009929053 0.0005723082 0.001348982 1.105273e-03 0.189291938 5.074523e-02
## 242 0.0103704041 0.0052593693 0.031857936 3.255164e-02 0.004047420 4.638932e-02
## 243 0.0103704041 0.0052593693 0.031857936 3.255164e-02 0.004047420 4.638932e-02
## 244 0.0103704041 0.0052593693 0.031857936 3.255164e-02 0.004047420 4.638932e-02
## 245 0.0103704041 0.0052593693 0.031857936 3.255164e-02 0.004047420 4.638932e-02
## 246 0.0103704041 0.0052593693 0.031857936 3.255164e-02 0.004047420 4.638932e-02
## 247 0.0703811778 0.0221981841 0.061323492 1.272831e-01 0.022737789 2.178512e-02
## 248 0.0703811778 0.0221981841 0.061323492 1.272831e-01 0.022737789 2.178512e-02
## 249 0.0703811778 0.0221981841 0.061323492 1.272831e-01 0.022737789 2.178512e-02
## 250 0.0009350882 0.0063463210 0.002891092 1.880720e-03 0.007356592 3.411266e-03
## 251 0.0009350882 0.0063463210 0.002891092 1.880720e-03 0.007356592 3.411266e-03
## 252 0.0009350882 0.0063463210 0.002891092 1.880720e-03 0.007356592 3.411266e-03
## 253 0.0009350882 0.0063463210 0.002891092 1.880720e-03 0.007356592 3.411266e-03
## 254 0.0096676661 0.0195380710 0.011278597 1.600913e-02 0.103795887 1.612318e-02
## 255 0.0039797502 0.0015814115 0.000297426 2.682258e-03 0.020225791 3.537293e-02
## 256 0.0039797502 0.0015814115 0.000297426 2.682258e-03 0.020225791 3.537293e-02
## 257 0.0039797502 0.0015814115 0.000297426 2.682258e-03 0.020225791 3.537293e-02
## 258 0.0039797502 0.0015814115 0.000297426 2.682258e-03 0.020225791 3.537293e-02
## 259 0.0039797502 0.0015814115 0.000297426 2.682258e-03 0.020225791 3.537293e-02
## 260 0.0164981637 0.0044400883 0.009637963 6.833658e-03 0.012954836 2.267827e-02
## 261 0.0164981637 0.0044400883 0.009637963 6.833658e-03 0.012954836 2.267827e-02
## 262 0.0098244200 0.0092334217 0.021345036 1.895826e-03 0.001544401 7.351538e-04
## 263 0.0062672802 0.0311440892 0.050813602 3.610160e-02 0.047210063 4.287143e-02
## 264 0.0062672802 0.0311440892 0.050813602 3.610160e-02 0.047210063 4.287143e-02
## 265 0.0062672802 0.0311440892 0.050813602 3.610160e-02 0.047210063 4.287143e-02
## 266 0.0421320768 0.0404445572 0.044437055 1.718702e-02 0.065990324 1.998062e-02
## 267 0.0421320768 0.0404445572 0.044437055 1.718702e-02 0.065990324 1.998062e-02
## 268 0.0421320768 0.0404445572 0.044437055 1.718702e-02 0.065990324 1.998062e-02
## 269 0.0421320768 0.0404445572 0.044437055 1.718702e-02 0.065990324 1.998062e-02
## 270 0.0421320768 0.0404445572 0.044437055 1.718702e-02 0.065990324 1.998062e-02
## 271 0.0421320768 0.0404445572 0.044437055 1.718702e-02 0.065990324 1.998062e-02
## 272 0.0293074183 0.0138591292 0.050849473 1.783339e-02 0.021232166 1.074281e-01
## 273 0.0293074183 0.0138591292 0.050849473 1.783339e-02 0.021232166 1.074281e-01
## 274 0.0126992441 0.0182902316 0.007103675 4.950981e-02 0.138303263 7.527578e-02
## 275 0.0126992441 0.0182902316 0.007103675 4.950981e-02 0.138303263 7.527578e-02
## 276 0.0126992441 0.0182902316 0.007103675 4.950981e-02 0.138303263 7.527578e-02
## 277 0.0182400411 0.0033538159 0.007092026 8.124803e-03 0.023396541 8.101307e-02
## 278 0.0182400411 0.0033538159 0.007092026 8.124803e-03 0.023396541 8.101307e-02
## 279 0.0182400411 0.0033538159 0.007092026 8.124803e-03 0.023396541 8.101307e-02
## 280 0.0182400411 0.0033538159 0.007092026 8.124803e-03 0.023396541 8.101307e-02
## 281 0.0182400411 0.0033538159 0.007092026 8.124803e-03 0.023396541 8.101307e-02
## 282 0.1001039444 0.1143130590 0.023796679 1.643779e-01 0.023606931 1.966041e-02
## 283 0.1001039444 0.1143130590 0.023796679 1.643779e-01 0.023606931 1.966041e-02
## 284 0.1001039444 0.1143130590 0.023796679 1.643779e-01 0.023606931 1.966041e-02
## 285 0.1001039444 0.1143130590 0.023796679 1.643779e-01 0.023606931 1.966041e-02
## 286 0.1001039444 0.1143130590 0.023796679 1.643779e-01 0.023606931 1.966041e-02
## 287 0.0857009319 0.0221878182 0.037783771 3.875800e-02 0.050438484 1.085865e-03
## 288 0.0857009319 0.0221878182 0.037783771 3.875800e-02 0.050438484 1.085865e-03
## 289 0.0447150347 0.0064723870 0.010019007 1.607964e-02 0.019049244 1.723120e-02
## 290 0.0447150347 0.0064723870 0.010019007 1.607964e-02 0.019049244 1.723120e-02
## 291 0.0447150347 0.0064723870 0.010019007 1.607964e-02 0.019049244 1.723120e-02
## 292 0.0447150347 0.0064723870 0.010019007 1.607964e-02 0.019049244 1.723120e-02
## 293 0.0447150347 0.0064723870 0.010019007 1.607964e-02 0.019049244 1.723120e-02
## 294 0.0447150347 0.0064723870 0.010019007 1.607964e-02 0.019049244 1.723120e-02
## 295 0.0547615496 0.1143353852 0.045839696 1.336731e-02 0.007772805 3.862116e-03
## 296 0.0547615496 0.1143353852 0.045839696 1.336731e-02 0.007772805 3.862116e-03
## 297 0.0547615496 0.1143353852 0.045839696 1.336731e-02 0.007772805 3.862116e-03
## 298 0.0510195627 0.0512574180 0.107942493 3.875533e-02 0.018684010 2.043458e-02
## 299 0.0510195627 0.0512574180 0.107942493 3.875533e-02 0.018684010 2.043458e-02
## 300 0.0510195627 0.0512574180 0.107942493 3.875533e-02 0.018684010 2.043458e-02
## 301 0.0361657145 0.0353433069 0.045247341 5.576294e-03 0.068962982 2.529177e-02
## 302 0.0361657145 0.0353433069 0.045247341 5.576294e-03 0.068962982 2.529177e-02
## 303 0.0297115338 0.0071574151 0.003992711 4.638426e-02 0.115127794 1.146392e-02
## 304 0.0297115338 0.0071574151 0.003992711 4.638426e-02 0.115127794 1.146392e-02
## 305 0.0297115338 0.0071574151 0.003992711 4.638426e-02 0.115127794 1.146392e-02
## 306 0.0297115338 0.0071574151 0.003992711 4.638426e-02 0.115127794 1.146392e-02
## 307 0.0297115338 0.0071574151 0.003992711 4.638426e-02 0.115127794 1.146392e-02
## 308 0.0075441559 0.0114149024 0.037270382 6.385090e-02 0.090244818 5.003924e-02
## 309 0.0075441559 0.0114149024 0.037270382 6.385090e-02 0.090244818 5.003924e-02
## 310 0.0075441559 0.0114149024 0.037270382 6.385090e-02 0.090244818 5.003924e-02
## 311 0.0061132795 0.0339185839 0.025446051 1.066712e-02 0.006943498 2.706091e-02
## 312 0.0061132795 0.0339185839 0.025446051 1.066712e-02 0.006943498 2.706091e-02
## 313 0.0061132795 0.0339185839 0.025446051 1.066712e-02 0.006943498 2.706091e-02
## 314 0.0061132795 0.0339185839 0.025446051 1.066712e-02 0.006943498 2.706091e-02
## 315 0.0061132795 0.0339185839 0.025446051 1.066712e-02 0.006943498 2.706091e-02
## 316 0.0061132795 0.0339185839 0.025446051 1.066712e-02 0.006943498 2.706091e-02
## 317 0.0370106665 0.0341893442 0.024762917 4.288248e-03 0.047297435 1.936900e-01
## 318 0.0370106665 0.0341893442 0.024762917 4.288248e-03 0.047297435 1.936900e-01
## 319 0.0370106665 0.0341893442 0.024762917 4.288248e-03 0.047297435 1.936900e-01
## 320 0.0911731324 0.1346098554 0.087709374 1.704258e-02 0.004143490 2.138789e-02
## 321 0.0911731324 0.1346098554 0.087709374 1.704258e-02 0.004143490 2.138789e-02
## 322 0.0911731324 0.1346098554 0.087709374 1.704258e-02 0.004143490 2.138789e-02
## 323 0.0911731324 0.1346098554 0.087709374 1.704258e-02 0.004143490 2.138789e-02
## 324 0.0217186027 0.0104273797 0.018321920 9.105918e-03 0.053215420 3.515628e-02
## 325 0.0217186027 0.0104273797 0.018321920 9.105918e-03 0.053215420 3.515628e-02
## 326 0.0217186027 0.0104273797 0.018321920 9.105918e-03 0.053215420 3.515628e-02
## 327 0.0217186027 0.0104273797 0.018321920 9.105918e-03 0.053215420 3.515628e-02
## 328 0.0217186027 0.0104273797 0.018321920 9.105918e-03 0.053215420 3.515628e-02
## W_E3 W_E4 W_S1 W_S2 W_S3 W_S4
## 1 1.014641e-01 0.040491446 0.0047115526 0.0071465714 0.002714608 0.0132805038
## 2 1.967053e-01 0.080122766 0.0174882882 0.0277535344 0.026976563 0.0140633829
## 3 1.967053e-01 0.080122766 0.0174882882 0.0277535344 0.026976563 0.0140633829
## 4 1.967053e-01 0.080122766 0.0174882882 0.0277535344 0.026976563 0.0140633829
## 5 1.967053e-01 0.080122766 0.0174882882 0.0277535344 0.026976563 0.0140633829
## 6 1.967053e-01 0.080122766 0.0174882882 0.0277535344 0.026976563 0.0140633829
## 7 6.366086e-02 0.103719805 0.0388568223 0.0311964576 0.033013438 0.0032164176
## 8 6.366086e-02 0.103719805 0.0388568223 0.0311964576 0.033013438 0.0032164176
## 9 1.529756e-02 0.004325194 0.0359797499 0.0317547911 0.003890364 0.0174357087
## 10 1.529756e-02 0.004325194 0.0359797499 0.0317547911 0.003890364 0.0174357087
## 11 1.529756e-02 0.004325194 0.0359797499 0.0317547911 0.003890364 0.0174357087
## 12 1.529756e-02 0.004325194 0.0359797499 0.0317547911 0.003890364 0.0174357087
## 13 1.950797e-02 0.015380515 0.0068057216 0.0001885888 0.001781435 0.0060938058
## 14 1.950797e-02 0.015380515 0.0068057216 0.0001885888 0.001781435 0.0060938058
## 15 1.950797e-02 0.015380515 0.0068057216 0.0001885888 0.001781435 0.0060938058
## 16 1.950797e-02 0.015380515 0.0068057216 0.0001885888 0.001781435 0.0060938058
## 17 1.950797e-02 0.015380515 0.0068057216 0.0001885888 0.001781435 0.0060938058
## 18 1.950797e-02 0.015380515 0.0068057216 0.0001885888 0.001781435 0.0060938058
## 19 2.304575e-02 0.027485073 0.0124034492 0.0091609126 0.010330106 0.0028304296
## 20 2.304575e-02 0.027485073 0.0124034492 0.0091609126 0.010330106 0.0028304296
## 21 2.304575e-02 0.027485073 0.0124034492 0.0091609126 0.010330106 0.0028304296
## 22 2.304575e-02 0.027485073 0.0124034492 0.0091609126 0.010330106 0.0028304296
## 23 2.304575e-02 0.027485073 0.0124034492 0.0091609126 0.010330106 0.0028304296
## 24 5.658296e-02 0.058967558 0.0207079838 0.0204143322 0.026354073 0.0101182315
## 25 5.658296e-02 0.058967558 0.0207079838 0.0204143322 0.026354073 0.0101182315
## 26 1.064629e-03 0.003608363 0.0165611925 0.0106099840 0.006319846 0.0318807706
## 27 1.064629e-03 0.003608363 0.0165611925 0.0106099840 0.006319846 0.0318807706
## 28 1.064629e-03 0.003608363 0.0165611925 0.0106099840 0.006319846 0.0318807706
## 29 2.695124e-02 0.029545152 0.0444186567 0.0060158677 0.062735892 0.0201315377
## 30 2.695124e-02 0.029545152 0.0444186567 0.0060158677 0.062735892 0.0201315377
## 31 2.695124e-02 0.029545152 0.0444186567 0.0060158677 0.062735892 0.0201315377
## 32 2.695124e-02 0.029545152 0.0444186567 0.0060158677 0.062735892 0.0201315377
## 33 2.695124e-02 0.029545152 0.0444186567 0.0060158677 0.062735892 0.0201315377
## 34 8.099913e-02 0.115523047 0.0014201616 0.0058612121 0.007087046 0.0055853676
## 35 8.099913e-02 0.115523047 0.0014201616 0.0058612121 0.007087046 0.0055853676
## 36 9.939231e-02 0.024054574 0.0013782631 0.0004284839 0.001369505 0.0005549455
## 37 9.939231e-02 0.024054574 0.0013782631 0.0004284839 0.001369505 0.0005549455
## 38 9.939231e-02 0.024054574 0.0013782631 0.0004284839 0.001369505 0.0005549455
## 39 9.939231e-02 0.024054574 0.0013782631 0.0004284839 0.001369505 0.0005549455
## 40 9.939231e-02 0.024054574 0.0013782631 0.0004284839 0.001369505 0.0005549455
## 41 9.939231e-02 0.024054574 0.0013782631 0.0004284839 0.001369505 0.0005549455
## 42 1.504227e-02 0.025881966 0.1126620253 0.0725368972 0.209206917 0.0348116584
## 43 1.504227e-02 0.025881966 0.1126620253 0.0725368972 0.209206917 0.0348116584
## 44 1.504227e-02 0.025881966 0.1126620253 0.0725368972 0.209206917 0.0348116584
## 45 1.504227e-02 0.025881966 0.1126620253 0.0725368972 0.209206917 0.0348116584
## 46 1.504227e-02 0.025881966 0.1126620253 0.0725368972 0.209206917 0.0348116584
## 47 2.023468e-03 0.003781195 0.0298413770 0.0260475489 0.015825330 0.0295249523
## 48 2.317278e-01 0.292292586 0.0010862727 0.0031705776 0.001252897 0.0005268040
## 49 2.317278e-01 0.292292586 0.0010862727 0.0031705776 0.001252897 0.0005268040
## 50 2.317278e-01 0.292292586 0.0010862727 0.0031705776 0.001252897 0.0005268040
## 51 2.317278e-01 0.292292586 0.0010862727 0.0031705776 0.001252897 0.0005268040
## 52 2.317278e-01 0.292292586 0.0010862727 0.0031705776 0.001252897 0.0005268040
## 53 2.317278e-01 0.292292586 0.0010862727 0.0031705776 0.001252897 0.0005268040
## 54 8.539417e-02 0.057468310 0.0854535770 0.1194666742 0.056699791 0.1613605881
## 55 8.539417e-02 0.057468310 0.0854535770 0.1194666742 0.056699791 0.1613605881
## 56 8.539417e-02 0.057468310 0.0854535770 0.1194666742 0.056699791 0.1613605881
## 57 2.375989e-02 0.084374959 0.0069557643 0.0825190381 0.016976020 0.0816218063
## 58 2.375989e-02 0.084374959 0.0069557643 0.0825190381 0.016976020 0.0816218063
## 59 2.375989e-02 0.084374959 0.0069557643 0.0825190381 0.016976020 0.0816218063
## 60 2.375989e-02 0.084374959 0.0069557643 0.0825190381 0.016976020 0.0816218063
## 61 2.375989e-02 0.084374959 0.0069557643 0.0825190381 0.016976020 0.0816218063
## 62 2.375989e-02 0.084374959 0.0069557643 0.0825190381 0.016976020 0.0816218063
## 63 4.709527e-03 0.003045407 0.0636333612 0.0484688077 0.087143223 0.0548419282
## 64 4.709527e-03 0.003045407 0.0636333612 0.0484688077 0.087143223 0.0548419282
## 65 4.709527e-03 0.003045407 0.0636333612 0.0484688077 0.087143223 0.0548419282
## 66 7.458195e-02 0.021371431 0.0134780514 0.0238438864 0.013442306 0.0078613999
## 67 7.458195e-02 0.021371431 0.0134780514 0.0238438864 0.013442306 0.0078613999
## 68 1.376201e-01 0.078906088 0.0016688808 0.0004767352 0.005769328 0.0038691961
## 69 1.376201e-01 0.078906088 0.0016688808 0.0004767352 0.005769328 0.0038691961
## 70 3.444711e-02 0.053559280 0.0330155733 0.0358204598 0.073230512 0.0538500830
## 71 3.444711e-02 0.053559280 0.0330155733 0.0358204598 0.073230512 0.0538500830
## 72 3.444711e-02 0.053559280 0.0330155733 0.0358204598 0.073230512 0.0538500830
## 73 3.444711e-02 0.053559280 0.0330155733 0.0358204598 0.073230512 0.0538500830
## 74 8.166399e-02 0.010892973 0.0563585517 0.0247127642 0.017031477 0.0366644534
## 75 8.166399e-02 0.010892973 0.0563585517 0.0247127642 0.017031477 0.0366644534
## 76 1.420511e-01 0.032094962 0.0227407713 0.0145832750 0.024528985 0.0060421634
## 77 3.489220e-02 0.046850512 0.0128931048 0.0033317819 0.006283207 0.0109053759
## 78 3.489220e-02 0.046850512 0.0128931048 0.0033317819 0.006283207 0.0109053759
## 79 3.489220e-02 0.046850512 0.0128931048 0.0033317819 0.006283207 0.0109053759
## 80 3.489220e-02 0.046850512 0.0128931048 0.0033317819 0.006283207 0.0109053759
## 81 3.489220e-02 0.046850512 0.0128931048 0.0033317819 0.006283207 0.0109053759
## 82 6.199675e-05 0.031937111 0.0013795999 0.0037038252 0.016256215 0.0071509114
## 83 6.199675e-05 0.031937111 0.0013795999 0.0037038252 0.016256215 0.0071509114
## 84 6.199675e-05 0.031937111 0.0013795999 0.0037038252 0.016256215 0.0071509114
## 85 6.199675e-05 0.031937111 0.0013795999 0.0037038252 0.016256215 0.0071509114
## 86 7.481730e-03 0.006114760 0.0290812628 0.0119065529 0.102267464 0.1094121917
## 87 5.963250e-02 0.220936820 0.0041452646 0.0049464926 0.009012087 0.0086772639
## 88 5.963250e-02 0.220936820 0.0041452646 0.0049464926 0.009012087 0.0086772639
## 89 2.076302e-02 0.017228020 0.0099739733 0.0756463870 0.063704570 0.0322721913
## 90 2.076302e-02 0.017228020 0.0099739733 0.0756463870 0.063704570 0.0322721913
## 91 4.423642e-02 0.028267381 0.0051436280 0.0248909497 0.003230573 0.0053232558
## 92 4.423642e-02 0.028267381 0.0051436280 0.0248909497 0.003230573 0.0053232558
## 93 4.423642e-02 0.028267381 0.0051436280 0.0248909497 0.003230573 0.0053232558
## 94 1.617974e-02 0.010153973 0.0198693591 0.0268369981 0.075904056 0.0484227318
## 95 1.617974e-02 0.010153973 0.0198693591 0.0268369981 0.075904056 0.0484227318
## 96 1.617974e-02 0.010153973 0.0198693591 0.0268369981 0.075904056 0.0484227318
## 97 1.617974e-02 0.010153973 0.0198693591 0.0268369981 0.075904056 0.0484227318
## 98 7.277528e-02 0.069912423 0.0048832699 0.0092056332 0.015780752 0.0162968501
## 99 7.277528e-02 0.069912423 0.0048832699 0.0092056332 0.015780752 0.0162968501
## 100 7.277528e-02 0.069912423 0.0048832699 0.0092056332 0.015780752 0.0162968501
## 101 7.277528e-02 0.069912423 0.0048832699 0.0092056332 0.015780752 0.0162968501
## 102 1.587808e-02 0.043903354 0.0078569630 0.0193028876 0.011400202 0.0190447846
## 103 8.423192e-02 0.103060720 0.0277429392 0.0029568408 0.005482146 0.0015404018
## 104 8.423192e-02 0.103060720 0.0277429392 0.0029568408 0.005482146 0.0015404018
## 105 8.423192e-02 0.103060720 0.0277429392 0.0029568408 0.005482146 0.0015404018
## 106 4.106336e-02 0.017302250 0.0509123314 0.0407656651 0.117187161 0.0383358350
## 107 4.106336e-02 0.017302250 0.0509123314 0.0407656651 0.117187161 0.0383358350
## 108 4.106336e-02 0.017302250 0.0509123314 0.0407656651 0.117187161 0.0383358350
## 109 1.323359e-02 0.004099495 0.0331507374 0.0277355104 0.032396967 0.1688727018
## 110 1.323359e-02 0.004099495 0.0331507374 0.0277355104 0.032396967 0.1688727018
## 111 1.323359e-02 0.004099495 0.0331507374 0.0277355104 0.032396967 0.1688727018
## 112 1.323359e-02 0.004099495 0.0331507374 0.0277355104 0.032396967 0.1688727018
## 113 1.323359e-02 0.004099495 0.0331507374 0.0277355104 0.032396967 0.1688727018
## 114 1.602371e-02 0.099751344 0.0033457093 0.0060128298 0.014365963 0.0049097391
## 115 1.602371e-02 0.099751344 0.0033457093 0.0060128298 0.014365963 0.0049097391
## 116 1.602371e-02 0.099751344 0.0033457093 0.0060128298 0.014365963 0.0049097391
## 117 1.602371e-02 0.099751344 0.0033457093 0.0060128298 0.014365963 0.0049097391
## 118 8.568601e-03 0.020742958 0.0351630159 0.0018757075 0.040215191 0.0038489542
## 119 8.568601e-03 0.020742958 0.0351630159 0.0018757075 0.040215191 0.0038489542
## 120 8.568601e-03 0.020742958 0.0351630159 0.0018757075 0.040215191 0.0038489542
## 121 8.568601e-03 0.020742958 0.0351630159 0.0018757075 0.040215191 0.0038489542
## 122 8.568601e-03 0.020742958 0.0351630159 0.0018757075 0.040215191 0.0038489542
## 123 8.399360e-02 0.111723300 0.0154174280 0.0210307082 0.028585615 0.0079587264
## 124 4.578357e-04 0.001742090 0.0050006226 0.0029889904 0.088902862 0.0478545546
## 125 4.578357e-04 0.001742090 0.0050006226 0.0029889904 0.088902862 0.0478545546
## 126 4.578357e-04 0.001742090 0.0050006226 0.0029889904 0.088902862 0.0478545546
## 127 4.578357e-04 0.001742090 0.0050006226 0.0029889904 0.088902862 0.0478545546
## 128 4.578357e-04 0.001742090 0.0050006226 0.0029889904 0.088902862 0.0478545546
## 129 6.079561e-02 0.057169322 0.0089015808 0.0061483646 0.015868935 0.0148434657
## 130 1.365557e-01 0.065202530 0.0177814170 0.0131756151 0.133911654 0.0060528906
## 131 1.365557e-01 0.065202530 0.0177814170 0.0131756151 0.133911654 0.0060528906
## 132 1.365557e-01 0.065202530 0.0177814170 0.0131756151 0.133911654 0.0060528906
## 133 1.365557e-01 0.065202530 0.0177814170 0.0131756151 0.133911654 0.0060528906
## 134 1.365557e-01 0.065202530 0.0177814170 0.0131756151 0.133911654 0.0060528906
## 135 5.378729e-02 0.006463973 0.0034451032 0.0050116822 0.003610533 0.0022321479
## 136 5.378729e-02 0.006463973 0.0034451032 0.0050116822 0.003610533 0.0022321479
## 137 5.378729e-02 0.006463973 0.0034451032 0.0050116822 0.003610533 0.0022321479
## 138 2.463631e-02 0.053308534 0.0256482240 0.0305311426 0.007284847 0.0082321752
## 139 1.203512e-02 0.022814678 0.0315780032 0.0192779727 0.028637383 0.0045944971
## 140 1.203512e-02 0.022814678 0.0315780032 0.0192779727 0.028637383 0.0045944971
## 141 8.860268e-03 0.006113168 0.0273360185 0.0299050980 0.005657296 0.0181876047
## 142 8.860268e-03 0.006113168 0.0273360185 0.0299050980 0.005657296 0.0181876047
## 143 5.231616e-03 0.010524386 0.0200916984 0.0290435283 0.073509239 0.0580091909
## 144 5.231616e-03 0.010524386 0.0200916984 0.0290435283 0.073509239 0.0580091909
## 145 5.231616e-03 0.010524386 0.0200916984 0.0290435283 0.073509239 0.0580091909
## 146 1.245625e-02 0.002515701 0.0073310829 0.0551418417 0.136449060 0.0347666115
## 147 7.401229e-03 0.007353677 0.0058093055 0.0052528760 0.001569073 0.0012403765
## 148 7.401229e-03 0.007353677 0.0058093055 0.0052528760 0.001569073 0.0012403765
## 149 7.401229e-03 0.007353677 0.0058093055 0.0052528760 0.001569073 0.0012403765
## 150 7.401229e-03 0.007353677 0.0058093055 0.0052528760 0.001569073 0.0012403765
## 151 9.752426e-03 0.073827332 0.0614992442 0.0194621289 0.032301610 0.0585006546
## 152 9.752426e-03 0.073827332 0.0614992442 0.0194621289 0.032301610 0.0585006546
## 153 9.752426e-03 0.073827332 0.0614992442 0.0194621289 0.032301610 0.0585006546
## 154 9.752426e-03 0.073827332 0.0614992442 0.0194621289 0.032301610 0.0585006546
## 155 6.912955e-02 0.021454954 0.0508794051 0.0588109300 0.017862745 0.0573292766
## 156 4.186786e-03 0.009827912 0.0189687112 0.0510835583 0.008339059 0.0750278296
## 157 4.186786e-03 0.009827912 0.0189687112 0.0510835583 0.008339059 0.0750278296
## 158 4.186786e-03 0.009827912 0.0189687112 0.0510835583 0.008339059 0.0750278296
## 159 4.186786e-03 0.009827912 0.0189687112 0.0510835583 0.008339059 0.0750278296
## 160 4.186786e-03 0.009827912 0.0189687112 0.0510835583 0.008339059 0.0750278296
## 161 4.186786e-03 0.009827912 0.0189687112 0.0510835583 0.008339059 0.0750278296
## 162 1.766357e-03 0.002174111 0.0180141915 0.1259372668 0.148076164 0.0041565686
## 163 1.766357e-03 0.002174111 0.0180141915 0.1259372668 0.148076164 0.0041565686
## 164 1.646039e-03 0.009490429 0.0255249875 0.0433335553 0.005128784 0.0214772315
## 165 1.646039e-03 0.009490429 0.0255249875 0.0433335553 0.005128784 0.0214772315
## 166 6.929635e-04 0.001821577 0.0421908835 0.0272412730 0.057696548 0.0255113619
## 167 6.929635e-04 0.001821577 0.0421908835 0.0272412730 0.057696548 0.0255113619
## 168 6.929635e-04 0.001821577 0.0421908835 0.0272412730 0.057696548 0.0255113619
## 169 6.929635e-04 0.001821577 0.0421908835 0.0272412730 0.057696548 0.0255113619
## 170 6.929635e-04 0.001821577 0.0421908835 0.0272412730 0.057696548 0.0255113619
## 171 6.929635e-04 0.001821577 0.0421908835 0.0272412730 0.057696548 0.0255113619
## 172 5.435904e-02 0.014878650 0.0004122096 0.0084051022 0.251818603 0.0533565534
## 173 5.435904e-02 0.014878650 0.0004122096 0.0084051022 0.251818603 0.0533565534
## 174 5.435904e-02 0.014878650 0.0004122096 0.0084051022 0.251818603 0.0533565534
## 175 2.366296e-02 0.053460303 0.0115117261 0.0123261163 0.056599588 0.0305215532
## 176 2.366296e-02 0.053460303 0.0115117261 0.0123261163 0.056599588 0.0305215532
## 177 2.366296e-02 0.053460303 0.0115117261 0.0123261163 0.056599588 0.0305215532
## 178 1.091432e-02 0.010828701 0.0130701677 0.0128143236 0.021579758 0.0201004222
## 179 1.091432e-02 0.010828701 0.0130701677 0.0128143236 0.021579758 0.0201004222
## 180 2.400981e-02 0.005046339 0.0131608764 0.0036524847 0.006099109 0.0034871752
## 181 2.400981e-02 0.005046339 0.0131608764 0.0036524847 0.006099109 0.0034871752
## 182 2.542958e-03 0.039218230 0.0046106352 0.0001101778 0.001351219 0.0042290568
## 183 2.542958e-03 0.039218230 0.0046106352 0.0001101778 0.001351219 0.0042290568
## 184 1.193063e-03 0.026163339 0.0592194800 0.0395332651 0.048439040 0.0252562238
## 185 1.193063e-03 0.026163339 0.0592194800 0.0395332651 0.048439040 0.0252562238
## 186 1.007765e-03 0.004295092 0.0022414374 0.0014341693 0.001449780 0.0003235656
## 187 1.007765e-03 0.004295092 0.0022414374 0.0014341693 0.001449780 0.0003235656
## 188 1.007765e-03 0.004295092 0.0022414374 0.0014341693 0.001449780 0.0003235656
## 189 1.007765e-03 0.004295092 0.0022414374 0.0014341693 0.001449780 0.0003235656
## 190 1.007765e-03 0.004295092 0.0022414374 0.0014341693 0.001449780 0.0003235656
## 191 1.007765e-03 0.004295092 0.0022414374 0.0014341693 0.001449780 0.0003235656
## 192 1.018096e-01 0.115979182 0.0120913463 0.0296282318 0.034839778 0.0090802700
## 193 1.018096e-01 0.115979182 0.0120913463 0.0296282318 0.034839778 0.0090802700
## 194 1.018096e-01 0.115979182 0.0120913463 0.0296282318 0.034839778 0.0090802700
## 195 1.018096e-01 0.115979182 0.0120913463 0.0296282318 0.034839778 0.0090802700
## 196 1.018096e-01 0.115979182 0.0120913463 0.0296282318 0.034839778 0.0090802700
## 197 4.260021e-02 0.046211621 0.0273774601 0.0191836981 0.009772479 0.0124411789
## 198 4.260021e-02 0.046211621 0.0273774601 0.0191836981 0.009772479 0.0124411789
## 199 7.874266e-03 0.013809380 0.0015210043 0.0017448086 0.002115746 0.0010049968
## 200 7.874266e-03 0.013809380 0.0015210043 0.0017448086 0.002115746 0.0010049968
## 201 7.874266e-03 0.013809380 0.0015210043 0.0017448086 0.002115746 0.0010049968
## 202 7.874266e-03 0.013809380 0.0015210043 0.0017448086 0.002115746 0.0010049968
## 203 1.200647e-01 0.113808524 0.0011812779 0.0119499431 0.006974499 0.0132782351
## 204 1.200647e-01 0.113808524 0.0011812779 0.0119499431 0.006974499 0.0132782351
## 205 1.200647e-01 0.113808524 0.0011812779 0.0119499431 0.006974499 0.0132782351
## 206 1.200647e-01 0.113808524 0.0011812779 0.0119499431 0.006974499 0.0132782351
## 207 2.567724e-02 0.048049446 0.0121410384 0.0157909598 0.022428463 0.0379294247
## 208 2.567724e-02 0.048049446 0.0121410384 0.0157909598 0.022428463 0.0379294247
## 209 2.366696e-01 0.161489162 0.0083104220 0.0174222997 0.005847716 0.0071369460
## 210 8.209864e-03 0.010901397 0.0996256540 0.2102660508 0.172368329 0.1399842901
## 211 8.209864e-03 0.010901397 0.0996256540 0.2102660508 0.172368329 0.1399842901
## 212 8.209864e-03 0.010901397 0.0996256540 0.2102660508 0.172368329 0.1399842901
## 213 2.256891e-02 0.018400558 0.0147557365 0.0207460647 0.018346070 0.0091077385
## 214 2.256891e-02 0.018400558 0.0147557365 0.0207460647 0.018346070 0.0091077385
## 215 2.256891e-02 0.018400558 0.0147557365 0.0207460647 0.018346070 0.0091077385
## 216 2.256891e-02 0.018400558 0.0147557365 0.0207460647 0.018346070 0.0091077385
## 217 2.477196e-02 0.030862895 0.0287324913 0.0141002972 0.030642170 0.0141963487
## 218 2.477196e-02 0.030862895 0.0287324913 0.0141002972 0.030642170 0.0141963487
## 219 2.477196e-02 0.030862895 0.0287324913 0.0141002972 0.030642170 0.0141963487
## 220 2.899744e-02 0.016495620 0.0372441773 0.0895763137 0.016492205 0.1009539532
## 221 2.899744e-02 0.016495620 0.0372441773 0.0895763137 0.016492205 0.1009539532
## 222 2.899744e-02 0.016495620 0.0372441773 0.0895763137 0.016492205 0.1009539532
## 223 2.899744e-02 0.016495620 0.0372441773 0.0895763137 0.016492205 0.1009539532
## 224 2.899744e-02 0.016495620 0.0372441773 0.0895763137 0.016492205 0.1009539532
## 225 2.771297e-02 0.117822939 0.0545234719 0.0211016670 0.016344143 0.0122898463
## 226 2.771297e-02 0.117822939 0.0545234719 0.0211016670 0.016344143 0.0122898463
## 227 3.807062e-02 0.053727346 0.1494512528 0.1526401221 0.221994569 0.1090592536
## 228 3.807062e-02 0.053727346 0.1494512528 0.1526401221 0.221994569 0.1090592536
## 229 3.807062e-02 0.053727346 0.1494512528 0.1526401221 0.221994569 0.1090592536
## 230 3.807062e-02 0.053727346 0.1494512528 0.1526401221 0.221994569 0.1090592536
## 231 1.987868e-02 0.015969003 0.0142821971 0.0197720967 0.002734420 0.0195382506
## 232 1.987868e-02 0.015969003 0.0142821971 0.0197720967 0.002734420 0.0195382506
## 233 1.987868e-02 0.015969003 0.0142821971 0.0197720967 0.002734420 0.0195382506
## 234 1.987868e-02 0.015969003 0.0142821971 0.0197720967 0.002734420 0.0195382506
## 235 3.144800e-03 0.018033996 0.0124485768 0.0097105431 0.056101845 0.0173008062
## 236 3.144800e-03 0.018033996 0.0124485768 0.0097105431 0.056101845 0.0173008062
## 237 3.144800e-03 0.018033996 0.0124485768 0.0097105431 0.056101845 0.0173008062
## 238 1.872860e-02 0.005389752 0.0069281145 0.0170459048 0.024232363 0.0177163143
## 239 1.872860e-02 0.005389752 0.0069281145 0.0170459048 0.024232363 0.0177163143
## 240 1.872860e-02 0.005389752 0.0069281145 0.0170459048 0.024232363 0.0177163143
## 241 1.158177e-01 0.187342054 0.0258297168 0.0105400332 0.020233675 0.0215569826
## 242 3.765445e-02 0.018288097 0.0311714223 0.0217506393 0.034412624 0.0119047429
## 243 3.765445e-02 0.018288097 0.0311714223 0.0217506393 0.034412624 0.0119047429
## 244 3.765445e-02 0.018288097 0.0311714223 0.0217506393 0.034412624 0.0119047429
## 245 3.765445e-02 0.018288097 0.0311714223 0.0217506393 0.034412624 0.0119047429
## 246 3.765445e-02 0.018288097 0.0311714223 0.0217506393 0.034412624 0.0119047429
## 247 1.033598e-01 0.037866733 0.0455977901 0.1579611005 0.120036535 0.0371025475
## 248 1.033598e-01 0.037866733 0.0455977901 0.1579611005 0.120036535 0.0371025475
## 249 1.033598e-01 0.037866733 0.0455977901 0.1579611005 0.120036535 0.0371025475
## 250 3.325210e-03 0.011360962 0.0284555322 0.0188639632 0.003433017 0.0061306371
## 251 3.325210e-03 0.011360962 0.0284555322 0.0188639632 0.003433017 0.0061306371
## 252 3.325210e-03 0.011360962 0.0284555322 0.0188639632 0.003433017 0.0061306371
## 253 3.325210e-03 0.011360962 0.0284555322 0.0188639632 0.003433017 0.0061306371
## 254 2.947485e-02 0.023073871 0.0088044798 0.0190618133 0.014931253 0.0005443606
## 255 2.259945e-02 0.042371717 0.1399233825 0.0579777281 0.177431144 0.0225011590
## 256 2.259945e-02 0.042371717 0.1399233825 0.0579777281 0.177431144 0.0225011590
## 257 2.259945e-02 0.042371717 0.1399233825 0.0579777281 0.177431144 0.0225011590
## 258 2.259945e-02 0.042371717 0.1399233825 0.0579777281 0.177431144 0.0225011590
## 259 2.259945e-02 0.042371717 0.1399233825 0.0579777281 0.177431144 0.0225011590
## 260 1.793280e-02 0.029103316 0.0072861772 0.0006553378 0.010122339 0.0039126749
## 261 1.793280e-02 0.029103316 0.0072861772 0.0006553378 0.010122339 0.0039126749
## 262 5.339737e-03 0.002049347 0.0045830982 0.0185463946 0.019931835 0.0236381704
## 263 2.079745e-01 0.094959000 0.0555811192 0.0923936626 0.033553904 0.1365143870
## 264 2.079745e-01 0.094959000 0.0555811192 0.0923936626 0.033553904 0.1365143870
## 265 2.079745e-01 0.094959000 0.0555811192 0.0923936626 0.033553904 0.1365143870
## 266 1.104980e-02 0.046329830 0.0703674228 0.0889602992 0.015273818 0.0287495374
## 267 1.104980e-02 0.046329830 0.0703674228 0.0889602992 0.015273818 0.0287495374
## 268 1.104980e-02 0.046329830 0.0703674228 0.0889602992 0.015273818 0.0287495374
## 269 1.104980e-02 0.046329830 0.0703674228 0.0889602992 0.015273818 0.0287495374
## 270 1.104980e-02 0.046329830 0.0703674228 0.0889602992 0.015273818 0.0287495374
## 271 1.104980e-02 0.046329830 0.0703674228 0.0889602992 0.015273818 0.0287495374
## 272 1.728922e-02 0.086554249 0.0146435287 0.0176255869 0.006457402 0.0063780420
## 273 1.728922e-02 0.086554249 0.0146435287 0.0176255869 0.006457402 0.0063780420
## 274 1.196717e-02 0.019460294 0.0052824186 0.0041367088 0.002587613 0.0067478477
## 275 1.196717e-02 0.019460294 0.0052824186 0.0041367088 0.002587613 0.0067478477
## 276 1.196717e-02 0.019460294 0.0052824186 0.0041367088 0.002587613 0.0067478477
## 277 7.038337e-03 0.126664572 0.0375198021 0.0613397037 0.012443349 0.0097592508
## 278 7.038337e-03 0.126664572 0.0375198021 0.0613397037 0.012443349 0.0097592508
## 279 7.038337e-03 0.126664572 0.0375198021 0.0613397037 0.012443349 0.0097592508
## 280 7.038337e-03 0.126664572 0.0375198021 0.0613397037 0.012443349 0.0097592508
## 281 7.038337e-03 0.126664572 0.0375198021 0.0613397037 0.012443349 0.0097592508
## 282 9.123827e-03 0.012657655 0.0325621234 0.0558825502 0.041256785 0.0725060691
## 283 9.123827e-03 0.012657655 0.0325621234 0.0558825502 0.041256785 0.0725060691
## 284 9.123827e-03 0.012657655 0.0325621234 0.0558825502 0.041256785 0.0725060691
## 285 9.123827e-03 0.012657655 0.0325621234 0.0558825502 0.041256785 0.0725060691
## 286 9.123827e-03 0.012657655 0.0325621234 0.0558825502 0.041256785 0.0725060691
## 287 3.786392e-02 0.037914081 0.0100304700 0.0188161121 0.021993214 0.0258427123
## 288 3.786392e-02 0.037914081 0.0100304700 0.0188161121 0.021993214 0.0258427123
## 289 1.445745e-02 0.002706264 0.0316902872 0.0753563260 0.075280872 0.0103244594
## 290 1.445745e-02 0.002706264 0.0316902872 0.0753563260 0.075280872 0.0103244594
## 291 1.445745e-02 0.002706264 0.0316902872 0.0753563260 0.075280872 0.0103244594
## 292 1.445745e-02 0.002706264 0.0316902872 0.0753563260 0.075280872 0.0103244594
## 293 1.445745e-02 0.002706264 0.0316902872 0.0753563260 0.075280872 0.0103244594
## 294 1.445745e-02 0.002706264 0.0316902872 0.0753563260 0.075280872 0.0103244594
## 295 2.976795e-03 0.003435648 0.0130958911 0.0509192822 0.018113250 0.0319259411
## 296 2.976795e-03 0.003435648 0.0130958911 0.0509192822 0.018113250 0.0319259411
## 297 2.976795e-03 0.003435648 0.0130958911 0.0509192822 0.018113250 0.0319259411
## 298 1.513094e-02 0.023867845 0.0027216909 0.0014458879 0.001449564 0.0023674188
## 299 1.513094e-02 0.023867845 0.0027216909 0.0014458879 0.001449564 0.0023674188
## 300 1.513094e-02 0.023867845 0.0027216909 0.0014458879 0.001449564 0.0023674188
## 301 1.422437e-02 0.041501874 0.0470857149 0.0309400083 0.026521235 0.0059534885
## 302 1.422437e-02 0.041501874 0.0470857149 0.0309400083 0.026521235 0.0059534885
## 303 1.071244e-02 0.032065527 0.0004985359 0.0011555684 0.001213983 0.0032774659
## 304 1.071244e-02 0.032065527 0.0004985359 0.0011555684 0.001213983 0.0032774659
## 305 1.071244e-02 0.032065527 0.0004985359 0.0011555684 0.001213983 0.0032774659
## 306 1.071244e-02 0.032065527 0.0004985359 0.0011555684 0.001213983 0.0032774659
## 307 1.071244e-02 0.032065527 0.0004985359 0.0011555684 0.001213983 0.0032774659
## 308 2.081203e-02 0.055873215 0.0794792834 0.0882538905 0.031596822 0.0767631174
## 309 2.081203e-02 0.055873215 0.0794792834 0.0882538905 0.031596822 0.0767631174
## 310 2.081203e-02 0.055873215 0.0794792834 0.0882538905 0.031596822 0.0767631174
## 311 2.122644e-02 0.005230158 0.0163661572 0.0003335082 0.013692660 0.0178106342
## 312 2.122644e-02 0.005230158 0.0163661572 0.0003335082 0.013692660 0.0178106342
## 313 2.122644e-02 0.005230158 0.0163661572 0.0003335082 0.013692660 0.0178106342
## 314 2.122644e-02 0.005230158 0.0163661572 0.0003335082 0.013692660 0.0178106342
## 315 2.122644e-02 0.005230158 0.0163661572 0.0003335082 0.013692660 0.0178106342
## 316 2.122644e-02 0.005230158 0.0163661572 0.0003335082 0.013692660 0.0178106342
## 317 3.358390e-02 0.080732125 0.0093126350 0.0140069390 0.007134948 0.0099837082
## 318 3.358390e-02 0.080732125 0.0093126350 0.0140069390 0.007134948 0.0099837082
## 319 3.358390e-02 0.080732125 0.0093126350 0.0140069390 0.007134948 0.0099837082
## 320 2.373095e-02 0.006368667 0.0057848883 0.0149727545 0.004841517 0.0068010664
## 321 2.373095e-02 0.006368667 0.0057848883 0.0149727545 0.004841517 0.0068010664
## 322 2.373095e-02 0.006368667 0.0057848883 0.0149727545 0.004841517 0.0068010664
## 323 2.373095e-02 0.006368667 0.0057848883 0.0149727545 0.004841517 0.0068010664
## 324 4.954991e-02 0.049366660 0.0065599127 0.0327192900 0.042908432 0.0321042987
## 325 4.954991e-02 0.049366660 0.0065599127 0.0327192900 0.042908432 0.0321042987
## 326 4.954991e-02 0.049366660 0.0065599127 0.0327192900 0.042908432 0.0321042987
## 327 4.954991e-02 0.049366660 0.0065599127 0.0327192900 0.042908432 0.0321042987
## 328 4.954991e-02 0.049366660 0.0065599127 0.0327192900 0.042908432 0.0321042987
## W_AF1 W_AF2 W_AF3 W_AF4 W_PV1
## 1 0.0315568470 0.0631084539 0.0265190189 0.0985093388 1.761918e-02
## 2 0.0524395115 0.0137138708 0.0377919530 0.0306680382 1.660232e-02
## 3 0.0524395115 0.0137138708 0.0377919530 0.0306680382 1.660232e-02
## 4 0.0524395115 0.0137138708 0.0377919530 0.0306680382 1.660232e-02
## 5 0.0524395115 0.0137138708 0.0377919530 0.0306680382 1.660232e-02
## 6 0.0524395115 0.0137138708 0.0377919530 0.0306680382 1.660232e-02
## 7 0.0546828839 0.0446600459 0.0905617071 0.0697384734 5.352206e-05
## 8 0.0546828839 0.0446600459 0.0905617071 0.0697384734 5.352206e-05
## 9 0.0787199714 0.0902925390 0.0830149027 0.0606862850 4.695418e-02
## 10 0.0787199714 0.0902925390 0.0830149027 0.0606862850 4.695418e-02
## 11 0.0787199714 0.0902925390 0.0830149027 0.0606862850 4.695418e-02
## 12 0.0787199714 0.0902925390 0.0830149027 0.0606862850 4.695418e-02
## 13 0.0439208341 0.0348853123 0.0182051514 0.0529193291 1.679976e-01
## 14 0.0439208341 0.0348853123 0.0182051514 0.0529193291 1.679976e-01
## 15 0.0439208341 0.0348853123 0.0182051514 0.0529193291 1.679976e-01
## 16 0.0439208341 0.0348853123 0.0182051514 0.0529193291 1.679976e-01
## 17 0.0439208341 0.0348853123 0.0182051514 0.0529193291 1.679976e-01
## 18 0.0439208341 0.0348853123 0.0182051514 0.0529193291 1.679976e-01
## 19 0.0178389674 0.0082643794 0.0218156645 0.0027119023 1.867413e-01
## 20 0.0178389674 0.0082643794 0.0218156645 0.0027119023 1.867413e-01
## 21 0.0178389674 0.0082643794 0.0218156645 0.0027119023 1.867413e-01
## 22 0.0178389674 0.0082643794 0.0218156645 0.0027119023 1.867413e-01
## 23 0.0178389674 0.0082643794 0.0218156645 0.0027119023 1.867413e-01
## 24 0.0864232671 0.0157583574 0.0479910812 0.0747272098 6.010945e-02
## 25 0.0864232671 0.0157583574 0.0479910812 0.0747272098 6.010945e-02
## 26 0.0811084777 0.1660724833 0.0555901860 0.0649893358 4.187706e-02
## 27 0.0811084777 0.1660724833 0.0555901860 0.0649893358 4.187706e-02
## 28 0.0811084777 0.1660724833 0.0555901860 0.0649893358 4.187706e-02
## 29 0.0828573779 0.0805277121 0.2496807660 0.0607319727 3.488608e-02
## 30 0.0828573779 0.0805277121 0.2496807660 0.0607319727 3.488608e-02
## 31 0.0828573779 0.0805277121 0.2496807660 0.0607319727 3.488608e-02
## 32 0.0828573779 0.0805277121 0.2496807660 0.0607319727 3.488608e-02
## 33 0.0828573779 0.0805277121 0.2496807660 0.0607319727 3.488608e-02
## 34 0.0607867534 0.0268226165 0.0244256164 0.0369940097 7.645657e-02
## 35 0.0607867534 0.0268226165 0.0244256164 0.0369940097 7.645657e-02
## 36 0.0049310750 0.0026709720 0.0003634384 0.0015292828 1.168110e-02
## 37 0.0049310750 0.0026709720 0.0003634384 0.0015292828 1.168110e-02
## 38 0.0049310750 0.0026709720 0.0003634384 0.0015292828 1.168110e-02
## 39 0.0049310750 0.0026709720 0.0003634384 0.0015292828 1.168110e-02
## 40 0.0049310750 0.0026709720 0.0003634384 0.0015292828 1.168110e-02
## 41 0.0049310750 0.0026709720 0.0003634384 0.0015292828 1.168110e-02
## 42 0.0022099404 0.0216097393 0.0367518786 0.0259768803 1.625155e-02
## 43 0.0022099404 0.0216097393 0.0367518786 0.0259768803 1.625155e-02
## 44 0.0022099404 0.0216097393 0.0367518786 0.0259768803 1.625155e-02
## 45 0.0022099404 0.0216097393 0.0367518786 0.0259768803 1.625155e-02
## 46 0.0022099404 0.0216097393 0.0367518786 0.0259768803 1.625155e-02
## 47 0.0595007722 0.0474535104 0.0747856161 0.0114665912 1.414256e-02
## 48 0.0008795604 0.0023584425 0.0035550069 0.0125618433 2.370674e-02
## 49 0.0008795604 0.0023584425 0.0035550069 0.0125618433 2.370674e-02
## 50 0.0008795604 0.0023584425 0.0035550069 0.0125618433 2.370674e-02
## 51 0.0008795604 0.0023584425 0.0035550069 0.0125618433 2.370674e-02
## 52 0.0008795604 0.0023584425 0.0035550069 0.0125618433 2.370674e-02
## 53 0.0008795604 0.0023584425 0.0035550069 0.0125618433 2.370674e-02
## 54 0.0241516105 0.0168194347 0.0250827290 0.0158309852 7.177285e-03
## 55 0.0241516105 0.0168194347 0.0250827290 0.0158309852 7.177285e-03
## 56 0.0241516105 0.0168194347 0.0250827290 0.0158309852 7.177285e-03
## 57 0.0011427672 0.0034301470 0.0039102979 0.0057695267 3.672567e-02
## 58 0.0011427672 0.0034301470 0.0039102979 0.0057695267 3.672567e-02
## 59 0.0011427672 0.0034301470 0.0039102979 0.0057695267 3.672567e-02
## 60 0.0011427672 0.0034301470 0.0039102979 0.0057695267 3.672567e-02
## 61 0.0011427672 0.0034301470 0.0039102979 0.0057695267 3.672567e-02
## 62 0.0011427672 0.0034301470 0.0039102979 0.0057695267 3.672567e-02
## 63 0.0667347461 0.1054125504 0.0465877251 0.0570967858 1.335093e-02
## 64 0.0667347461 0.1054125504 0.0465877251 0.0570967858 1.335093e-02
## 65 0.0667347461 0.1054125504 0.0465877251 0.0570967858 1.335093e-02
## 66 0.0029456633 0.0123146206 0.0082659580 0.0073020334 5.484024e-03
## 67 0.0029456633 0.0123146206 0.0082659580 0.0073020334 5.484024e-03
## 68 0.0140170176 0.0091234352 0.0161527518 0.0050267666 3.173677e-03
## 69 0.0140170176 0.0091234352 0.0161527518 0.0050267666 3.173677e-03
## 70 0.0354259943 0.0033598044 0.0083328908 0.0632128073 2.640079e-02
## 71 0.0354259943 0.0033598044 0.0083328908 0.0632128073 2.640079e-02
## 72 0.0354259943 0.0033598044 0.0083328908 0.0632128073 2.640079e-02
## 73 0.0354259943 0.0033598044 0.0083328908 0.0632128073 2.640079e-02
## 74 0.0008028638 0.0006140606 0.0002858708 0.0022270621 6.539016e-02
## 75 0.0008028638 0.0006140606 0.0002858708 0.0022270621 6.539016e-02
## 76 0.0384875661 0.0341928794 0.0284192332 0.0227088376 6.001528e-02
## 77 0.0151602360 0.0517291429 0.0283823184 0.0377701425 1.360633e-02
## 78 0.0151602360 0.0517291429 0.0283823184 0.0377701425 1.360633e-02
## 79 0.0151602360 0.0517291429 0.0283823184 0.0377701425 1.360633e-02
## 80 0.0151602360 0.0517291429 0.0283823184 0.0377701425 1.360633e-02
## 81 0.0151602360 0.0517291429 0.0283823184 0.0377701425 1.360633e-02
## 82 0.0360430198 0.1092025479 0.0821733433 0.0179582524 3.391960e-02
## 83 0.0360430198 0.1092025479 0.0821733433 0.0179582524 3.391960e-02
## 84 0.0360430198 0.1092025479 0.0821733433 0.0179582524 3.391960e-02
## 85 0.0360430198 0.1092025479 0.0821733433 0.0179582524 3.391960e-02
## 86 0.0219738813 0.0368674549 0.0996879666 0.1057407907 4.194381e-02
## 87 0.0108846834 0.0010988117 0.0028490809 0.0105506520 8.052053e-02
## 88 0.0108846834 0.0010988117 0.0028490809 0.0105506520 8.052053e-02
## 89 0.0174438343 0.0101554687 0.0137705786 0.0318549789 3.549033e-02
## 90 0.0174438343 0.0101554687 0.0137705786 0.0318549789 3.549033e-02
## 91 0.0043304087 0.0143116201 0.0240732838 0.0119130295 1.672125e-02
## 92 0.0043304087 0.0143116201 0.0240732838 0.0119130295 1.672125e-02
## 93 0.0043304087 0.0143116201 0.0240732838 0.0119130295 1.672125e-02
## 94 0.0648474208 0.0297653283 0.0492135259 0.0459554673 1.786243e-04
## 95 0.0648474208 0.0297653283 0.0492135259 0.0459554673 1.786243e-04
## 96 0.0648474208 0.0297653283 0.0492135259 0.0459554673 1.786243e-04
## 97 0.0648474208 0.0297653283 0.0492135259 0.0459554673 1.786243e-04
## 98 0.1012420206 0.0319209382 0.0333480357 0.0581235442 1.561188e-02
## 99 0.1012420206 0.0319209382 0.0333480357 0.0581235442 1.561188e-02
## 100 0.1012420206 0.0319209382 0.0333480357 0.0581235442 1.561188e-02
## 101 0.1012420206 0.0319209382 0.0333480357 0.0581235442 1.561188e-02
## 102 0.1153346547 0.0218625308 0.0181100462 0.0103075767 2.716112e-03
## 103 0.0124734730 0.0065751676 0.0177898649 0.0349234876 5.277512e-03
## 104 0.0124734730 0.0065751676 0.0177898649 0.0349234876 5.277512e-03
## 105 0.0124734730 0.0065751676 0.0177898649 0.0349234876 5.277512e-03
## 106 0.0527332735 0.1426705048 0.0476379554 0.1021221289 2.386785e-04
## 107 0.0527332735 0.1426705048 0.0476379554 0.1021221289 2.386785e-04
## 108 0.0527332735 0.1426705048 0.0476379554 0.1021221289 2.386785e-04
## 109 0.0621016620 0.0226908732 0.0443956271 0.0556679993 3.493213e-03
## 110 0.0621016620 0.0226908732 0.0443956271 0.0556679993 3.493213e-03
## 111 0.0621016620 0.0226908732 0.0443956271 0.0556679993 3.493213e-03
## 112 0.0621016620 0.0226908732 0.0443956271 0.0556679993 3.493213e-03
## 113 0.0621016620 0.0226908732 0.0443956271 0.0556679993 3.493213e-03
## 114 0.1225872118 0.0288812087 0.0740428607 0.1728983518 7.396677e-03
## 115 0.1225872118 0.0288812087 0.0740428607 0.1728983518 7.396677e-03
## 116 0.1225872118 0.0288812087 0.0740428607 0.1728983518 7.396677e-03
## 117 0.1225872118 0.0288812087 0.0740428607 0.1728983518 7.396677e-03
## 118 0.0177854110 0.0246312931 0.0087459423 0.0483235822 3.187777e-02
## 119 0.0177854110 0.0246312931 0.0087459423 0.0483235822 3.187777e-02
## 120 0.0177854110 0.0246312931 0.0087459423 0.0483235822 3.187777e-02
## 121 0.0177854110 0.0246312931 0.0087459423 0.0483235822 3.187777e-02
## 122 0.0177854110 0.0246312931 0.0087459423 0.0483235822 3.187777e-02
## 123 0.0311512823 0.0153305196 0.0178353345 0.0341589324 4.279246e-02
## 124 0.0072779541 0.0070668186 0.0239441216 0.0078107724 1.161892e-03
## 125 0.0072779541 0.0070668186 0.0239441216 0.0078107724 1.161892e-03
## 126 0.0072779541 0.0070668186 0.0239441216 0.0078107724 1.161892e-03
## 127 0.0072779541 0.0070668186 0.0239441216 0.0078107724 1.161892e-03
## 128 0.0072779541 0.0070668186 0.0239441216 0.0078107724 1.161892e-03
## 129 0.0255200446 0.0618412023 0.0574927047 0.0216314021 9.858844e-03
## 130 0.0452752212 0.0496253905 0.0068002433 0.0372468734 7.420995e-03
## 131 0.0452752212 0.0496253905 0.0068002433 0.0372468734 7.420995e-03
## 132 0.0452752212 0.0496253905 0.0068002433 0.0372468734 7.420995e-03
## 133 0.0452752212 0.0496253905 0.0068002433 0.0372468734 7.420995e-03
## 134 0.0452752212 0.0496253905 0.0068002433 0.0372468734 7.420995e-03
## 135 0.0965995234 0.1211719813 0.0828091321 0.0486125230 6.788869e-03
## 136 0.0965995234 0.1211719813 0.0828091321 0.0486125230 6.788869e-03
## 137 0.0965995234 0.1211719813 0.0828091321 0.0486125230 6.788869e-03
## 138 0.0352936928 0.0468966747 0.0104105698 0.0332475625 1.582141e-01
## 139 0.2087306599 0.1799671617 0.0330138193 0.1218944423 4.861940e-03
## 140 0.2087306599 0.1799671617 0.0330138193 0.1218944423 4.861940e-03
## 141 0.0159606928 0.0272743154 0.0048503394 0.0173165849 3.354439e-02
## 142 0.0159606928 0.0272743154 0.0048503394 0.0173165849 3.354439e-02
## 143 0.0586218062 0.0231576996 0.0395590538 0.0093937789 3.338730e-02
## 144 0.0586218062 0.0231576996 0.0395590538 0.0093937789 3.338730e-02
## 145 0.0586218062 0.0231576996 0.0395590538 0.0093937789 3.338730e-02
## 146 0.0369866677 0.0605247642 0.0020233604 0.0405225488 3.955655e-03
## 147 0.0148701330 0.0549555199 0.1163958397 0.0191088385 1.015556e-01
## 148 0.0148701330 0.0549555199 0.1163958397 0.0191088385 1.015556e-01
## 149 0.0148701330 0.0549555199 0.1163958397 0.0191088385 1.015556e-01
## 150 0.0148701330 0.0549555199 0.1163958397 0.0191088385 1.015556e-01
## 151 0.0213700577 0.0298017702 0.0441097307 0.0325207614 8.298113e-03
## 152 0.0213700577 0.0298017702 0.0441097307 0.0325207614 8.298113e-03
## 153 0.0213700577 0.0298017702 0.0441097307 0.0325207614 8.298113e-03
## 154 0.0213700577 0.0298017702 0.0441097307 0.0325207614 8.298113e-03
## 155 0.0057207134 0.0022696367 0.0006747184 0.0024320150 8.525112e-03
## 156 0.0167362508 0.0094742249 0.0153554287 0.0305466283 3.834885e-02
## 157 0.0167362508 0.0094742249 0.0153554287 0.0305466283 3.834885e-02
## 158 0.0167362508 0.0094742249 0.0153554287 0.0305466283 3.834885e-02
## 159 0.0167362508 0.0094742249 0.0153554287 0.0305466283 3.834885e-02
## 160 0.0167362508 0.0094742249 0.0153554287 0.0305466283 3.834885e-02
## 161 0.0167362508 0.0094742249 0.0153554287 0.0305466283 3.834885e-02
## 162 0.0473261886 0.0769980517 0.0846719537 0.0429703364 2.367980e-02
## 163 0.0473261886 0.0769980517 0.0846719537 0.0429703364 2.367980e-02
## 164 0.0366661538 0.0043527992 0.0265582035 0.0170787604 3.796489e-02
## 165 0.0366661538 0.0043527992 0.0265582035 0.0170787604 3.796489e-02
## 166 0.0425258473 0.0688671225 0.0881780987 0.0691901757 3.383333e-02
## 167 0.0425258473 0.0688671225 0.0881780987 0.0691901757 3.383333e-02
## 168 0.0425258473 0.0688671225 0.0881780987 0.0691901757 3.383333e-02
## 169 0.0425258473 0.0688671225 0.0881780987 0.0691901757 3.383333e-02
## 170 0.0425258473 0.0688671225 0.0881780987 0.0691901757 3.383333e-02
## 171 0.0425258473 0.0688671225 0.0881780987 0.0691901757 3.383333e-02
## 172 0.0061849296 0.0014980008 0.0137105358 0.0085938296 2.424602e-04
## 173 0.0061849296 0.0014980008 0.0137105358 0.0085938296 2.424602e-04
## 174 0.0061849296 0.0014980008 0.0137105358 0.0085938296 2.424602e-04
## 175 0.0224955800 0.0031408079 0.0089366693 0.0042061276 1.164963e-02
## 176 0.0224955800 0.0031408079 0.0089366693 0.0042061276 1.164963e-02
## 177 0.0224955800 0.0031408079 0.0089366693 0.0042061276 1.164963e-02
## 178 0.1225449436 0.0766423716 0.0788436606 0.0201824843 1.143624e-02
## 179 0.1225449436 0.0766423716 0.0788436606 0.0201824843 1.143624e-02
## 180 0.0170987090 0.0109323849 0.0157727151 0.0035951902 3.579084e-02
## 181 0.0170987090 0.0109323849 0.0157727151 0.0035951902 3.579084e-02
## 182 0.0495446509 0.1824038391 0.0363371363 0.0463177303 1.577882e-02
## 183 0.0495446509 0.1824038391 0.0363371363 0.0463177303 1.577882e-02
## 184 0.0457528915 0.0397242209 0.0501456160 0.0363266860 3.127850e-02
## 185 0.0457528915 0.0397242209 0.0501456160 0.0363266860 3.127850e-02
## 186 0.0440644050 0.0198325685 0.0172837406 0.0532122073 4.893752e-02
## 187 0.0440644050 0.0198325685 0.0172837406 0.0532122073 4.893752e-02
## 188 0.0440644050 0.0198325685 0.0172837406 0.0532122073 4.893752e-02
## 189 0.0440644050 0.0198325685 0.0172837406 0.0532122073 4.893752e-02
## 190 0.0440644050 0.0198325685 0.0172837406 0.0532122073 4.893752e-02
## 191 0.0440644050 0.0198325685 0.0172837406 0.0532122073 4.893752e-02
## 192 0.0052241257 0.0101749182 0.0235192469 0.0233049831 4.031460e-03
## 193 0.0052241257 0.0101749182 0.0235192469 0.0233049831 4.031460e-03
## 194 0.0052241257 0.0101749182 0.0235192469 0.0233049831 4.031460e-03
## 195 0.0052241257 0.0101749182 0.0235192469 0.0233049831 4.031460e-03
## 196 0.0052241257 0.0101749182 0.0235192469 0.0233049831 4.031460e-03
## 197 0.0295440495 0.0108104891 0.0558573619 0.0460897994 5.833342e-02
## 198 0.0295440495 0.0108104891 0.0558573619 0.0460897994 5.833342e-02
## 199 0.0572374987 0.0383632778 0.0572290827 0.0388069930 1.585698e-02
## 200 0.0572374987 0.0383632778 0.0572290827 0.0388069930 1.585698e-02
## 201 0.0572374987 0.0383632778 0.0572290827 0.0388069930 1.585698e-02
## 202 0.0572374987 0.0383632778 0.0572290827 0.0388069930 1.585698e-02
## 203 0.0911162084 0.0369572523 0.0146233111 0.0997334638 8.380905e-02
## 204 0.0911162084 0.0369572523 0.0146233111 0.0997334638 8.380905e-02
## 205 0.0911162084 0.0369572523 0.0146233111 0.0997334638 8.380905e-02
## 206 0.0911162084 0.0369572523 0.0146233111 0.0997334638 8.380905e-02
## 207 0.1212247504 0.0972472231 0.1165513771 0.0088979503 7.973839e-04
## 208 0.1212247504 0.0972472231 0.1165513771 0.0088979503 7.973839e-04
## 209 0.0187169394 0.0194869157 0.0359237894 0.0280447693 1.974285e-02
## 210 0.0069529677 0.0028550100 0.0107559419 0.0142403026 3.266493e-03
## 211 0.0069529677 0.0028550100 0.0107559419 0.0142403026 3.266493e-03
## 212 0.0069529677 0.0028550100 0.0107559419 0.0142403026 3.266493e-03
## 213 0.0211089083 0.0253519121 0.0849604980 0.0488636048 7.849297e-03
## 214 0.0211089083 0.0253519121 0.0849604980 0.0488636048 7.849297e-03
## 215 0.0211089083 0.0253519121 0.0849604980 0.0488636048 7.849297e-03
## 216 0.0211089083 0.0253519121 0.0849604980 0.0488636048 7.849297e-03
## 217 0.0357612964 0.0608965294 0.0498565420 0.0312061112 7.484563e-02
## 218 0.0357612964 0.0608965294 0.0498565420 0.0312061112 7.484563e-02
## 219 0.0357612964 0.0608965294 0.0498565420 0.0312061112 7.484563e-02
## 220 0.0075149174 0.0255615348 0.0251728028 0.0758018926 3.436843e-02
## 221 0.0075149174 0.0255615348 0.0251728028 0.0758018926 3.436843e-02
## 222 0.0075149174 0.0255615348 0.0251728028 0.0758018926 3.436843e-02
## 223 0.0075149174 0.0255615348 0.0251728028 0.0758018926 3.436843e-02
## 224 0.0075149174 0.0255615348 0.0251728028 0.0758018926 3.436843e-02
## 225 0.0143686049 0.0203219752 0.0715840022 0.0107088329 1.332127e-02
## 226 0.0143686049 0.0203219752 0.0715840022 0.0107088329 1.332127e-02
## 227 0.0014609150 0.0057897638 0.0014393243 0.0032625099 1.166685e-02
## 228 0.0014609150 0.0057897638 0.0014393243 0.0032625099 1.166685e-02
## 229 0.0014609150 0.0057897638 0.0014393243 0.0032625099 1.166685e-02
## 230 0.0014609150 0.0057897638 0.0014393243 0.0032625099 1.166685e-02
## 231 0.0406276962 0.0642938084 0.0125412975 0.0750262912 1.170692e-02
## 232 0.0406276962 0.0642938084 0.0125412975 0.0750262912 1.170692e-02
## 233 0.0406276962 0.0642938084 0.0125412975 0.0750262912 1.170692e-02
## 234 0.0406276962 0.0642938084 0.0125412975 0.0750262912 1.170692e-02
## 235 0.0154185782 0.0079655158 0.0116340300 0.0031648836 8.234423e-03
## 236 0.0154185782 0.0079655158 0.0116340300 0.0031648836 8.234423e-03
## 237 0.0154185782 0.0079655158 0.0116340300 0.0031648836 8.234423e-03
## 238 0.0420648553 0.0150217713 0.0209004990 0.0522910280 1.907228e-01
## 239 0.0420648553 0.0150217713 0.0209004990 0.0522910280 1.907228e-01
## 240 0.0420648553 0.0150217713 0.0209004990 0.0522910280 1.907228e-01
## 241 0.0192013105 0.0728495186 0.0336055407 0.0153158561 3.254920e-02
## 242 0.0643328686 0.0155597303 0.0349680074 0.0186943241 7.151547e-03
## 243 0.0643328686 0.0155597303 0.0349680074 0.0186943241 7.151547e-03
## 244 0.0643328686 0.0155597303 0.0349680074 0.0186943241 7.151547e-03
## 245 0.0643328686 0.0155597303 0.0349680074 0.0186943241 7.151547e-03
## 246 0.0643328686 0.0155597303 0.0349680074 0.0186943241 7.151547e-03
## 247 0.0091153701 0.0045174386 0.0030269808 0.0087875280 1.890258e-03
## 248 0.0091153701 0.0045174386 0.0030269808 0.0087875280 1.890258e-03
## 249 0.0091153701 0.0045174386 0.0030269808 0.0087875280 1.890258e-03
## 250 0.0795642575 0.0451986197 0.1483980978 0.1141248310 3.444376e-02
## 251 0.0795642575 0.0451986197 0.1483980978 0.1141248310 3.444376e-02
## 252 0.0795642575 0.0451986197 0.1483980978 0.1141248310 3.444376e-02
## 253 0.0795642575 0.0451986197 0.1483980978 0.1141248310 3.444376e-02
## 254 0.0167688092 0.0840401252 0.0369175718 0.0404646684 1.669049e-01
## 255 0.0757028790 0.0215308798 0.0264293419 0.0207471782 6.581960e-02
## 256 0.0757028790 0.0215308798 0.0264293419 0.0207471782 6.581960e-02
## 257 0.0757028790 0.0215308798 0.0264293419 0.0207471782 6.581960e-02
## 258 0.0757028790 0.0215308798 0.0264293419 0.0207471782 6.581960e-02
## 259 0.0757028790 0.0215308798 0.0264293419 0.0207471782 6.581960e-02
## 260 0.0082649675 0.0692462957 0.0563858220 0.0215466642 9.249250e-03
## 261 0.0082649675 0.0692462957 0.0563858220 0.0215466642 9.249250e-03
## 262 0.0027982382 0.0081621867 0.0166203157 0.0061970856 1.239137e-01
## 263 0.0026599986 0.0024746673 0.0056623243 0.0129237708 1.212061e-02
## 264 0.0026599986 0.0024746673 0.0056623243 0.0129237708 1.212061e-02
## 265 0.0026599986 0.0024746673 0.0056623243 0.0129237708 1.212061e-02
## 266 0.0127690628 0.0150552769 0.0193775878 0.0004212275 1.385942e-03
## 267 0.0127690628 0.0150552769 0.0193775878 0.0004212275 1.385942e-03
## 268 0.0127690628 0.0150552769 0.0193775878 0.0004212275 1.385942e-03
## 269 0.0127690628 0.0150552769 0.0193775878 0.0004212275 1.385942e-03
## 270 0.0127690628 0.0150552769 0.0193775878 0.0004212275 1.385942e-03
## 271 0.0127690628 0.0150552769 0.0193775878 0.0004212275 1.385942e-03
## 272 0.0554936170 0.0599326719 0.0247335516 0.0370399982 1.092886e-02
## 273 0.0554936170 0.0599326719 0.0247335516 0.0370399982 1.092886e-02
## 274 0.0378950091 0.0668665969 0.0137842853 0.0262447295 3.364661e-03
## 275 0.0378950091 0.0668665969 0.0137842853 0.0262447295 3.364661e-03
## 276 0.0378950091 0.0668665969 0.0137842853 0.0262447295 3.364661e-03
## 277 0.1013249627 0.0822274770 0.0402905670 0.0329035609 6.491840e-02
## 278 0.1013249627 0.0822274770 0.0402905670 0.0329035609 6.491840e-02
## 279 0.1013249627 0.0822274770 0.0402905670 0.0329035609 6.491840e-02
## 280 0.1013249627 0.0822274770 0.0402905670 0.0329035609 6.491840e-02
## 281 0.1013249627 0.0822274770 0.0402905670 0.0329035609 6.491840e-02
## 282 0.0122396850 0.0462799406 0.0264871715 0.0024891957 1.460812e-02
## 283 0.0122396850 0.0462799406 0.0264871715 0.0024891957 1.460812e-02
## 284 0.0122396850 0.0462799406 0.0264871715 0.0024891957 1.460812e-02
## 285 0.0122396850 0.0462799406 0.0264871715 0.0024891957 1.460812e-02
## 286 0.0122396850 0.0462799406 0.0264871715 0.0024891957 1.460812e-02
## 287 0.0099796472 0.0108990533 0.0390446526 0.0098464711 6.805809e-02
## 288 0.0099796472 0.0108990533 0.0390446526 0.0098464711 6.805809e-02
## 289 0.2051523364 0.0468447493 0.0772687737 0.1229826883 4.335039e-02
## 290 0.2051523364 0.0468447493 0.0772687737 0.1229826883 4.335039e-02
## 291 0.2051523364 0.0468447493 0.0772687737 0.1229826883 4.335039e-02
## 292 0.2051523364 0.0468447493 0.0772687737 0.1229826883 4.335039e-02
## 293 0.2051523364 0.0468447493 0.0772687737 0.1229826883 4.335039e-02
## 294 0.2051523364 0.0468447493 0.0772687737 0.1229826883 4.335039e-02
## 295 0.0644112328 0.0214798021 0.0265072117 0.0285211469 4.113063e-02
## 296 0.0644112328 0.0214798021 0.0265072117 0.0285211469 4.113063e-02
## 297 0.0644112328 0.0214798021 0.0265072117 0.0285211469 4.113063e-02
## 298 0.0543286026 0.0249448117 0.0284007542 0.0341200696 2.806200e-02
## 299 0.0543286026 0.0249448117 0.0284007542 0.0341200696 2.806200e-02
## 300 0.0543286026 0.0249448117 0.0284007542 0.0341200696 2.806200e-02
## 301 0.0421829307 0.0281549893 0.0299162037 0.0306516135 1.591282e-01
## 302 0.0421829307 0.0281549893 0.0299162037 0.0306516135 1.591282e-01
## 303 0.0046765300 0.0208044925 0.0162562181 0.0100945758 1.736730e-01
## 304 0.0046765300 0.0208044925 0.0162562181 0.0100945758 1.736730e-01
## 305 0.0046765300 0.0208044925 0.0162562181 0.0100945758 1.736730e-01
## 306 0.0046765300 0.0208044925 0.0162562181 0.0100945758 1.736730e-01
## 307 0.0046765300 0.0208044925 0.0162562181 0.0100945758 1.736730e-01
## 308 0.0083667739 0.0045639710 0.0099688134 0.0025527818 4.999439e-02
## 309 0.0083667739 0.0045639710 0.0099688134 0.0025527818 4.999439e-02
## 310 0.0083667739 0.0045639710 0.0099688134 0.0025527818 4.999439e-02
## 311 0.0047400494 0.0010652504 0.0017577805 0.0013394577 1.705174e-01
## 312 0.0047400494 0.0010652504 0.0017577805 0.0013394577 1.705174e-01
## 313 0.0047400494 0.0010652504 0.0017577805 0.0013394577 1.705174e-01
## 314 0.0047400494 0.0010652504 0.0017577805 0.0013394577 1.705174e-01
## 315 0.0047400494 0.0010652504 0.0017577805 0.0013394577 1.705174e-01
## 316 0.0047400494 0.0010652504 0.0017577805 0.0013394577 1.705174e-01
## 317 0.0851522611 0.0850297383 0.0734949439 0.0629901619 1.172651e-02
## 318 0.0851522611 0.0850297383 0.0734949439 0.0629901619 1.172651e-02
## 319 0.0851522611 0.0850297383 0.0734949439 0.0629901619 1.172651e-02
## 320 0.0230901249 0.0184029994 0.0967865514 0.0330681029 9.334652e-02
## 321 0.0230901249 0.0184029994 0.0967865514 0.0330681029 9.334652e-02
## 322 0.0230901249 0.0184029994 0.0967865514 0.0330681029 9.334652e-02
## 323 0.0230901249 0.0184029994 0.0967865514 0.0330681029 9.334652e-02
## 324 0.2493633514 0.0646901689 0.0360366419 0.0194571182 7.757753e-02
## 325 0.2493633514 0.0646901689 0.0360366419 0.0194571182 7.757753e-02
## 326 0.2493633514 0.0646901689 0.0360366419 0.0194571182 7.757753e-02
## 327 0.2493633514 0.0646901689 0.0360366419 0.0194571182 7.757753e-02
## 328 0.2493633514 0.0646901689 0.0360366419 0.0194571182 7.757753e-02
## W_PV2 W_PV3 W_PV4 W_SS_Effect LLMWeight_Claude
## 1 0.0011823954 0.0141586832 0.0090260040 0.342493958 0.21355603
## 2 0.0152965362 0.0104586243 0.0225611942 0.328299654 0.20997050
## 3 0.0152965362 0.0104586243 0.0225611942 0.328299654 0.20997050
## 4 0.0152965362 0.0104586243 0.0225611942 0.328299654 0.20997050
## 5 0.0152965362 0.0104586243 0.0225611942 0.328299654 0.20997050
## 6 0.0152965362 0.0104586243 0.0225611942 0.328299654 0.20997050
## 7 0.0004045799 0.0007249126 0.0003040345 0.019513037 0.26838796
## 8 0.0004045799 0.0007249126 0.0003040345 0.019513037 0.26838796
## 9 0.0219093636 0.1482251061 0.0842046966 0.174146108 0.20834181
## 10 0.0219093636 0.1482251061 0.0842046966 0.174146108 0.20834181
## 11 0.0219093636 0.1482251061 0.0842046966 0.174146108 0.20834181
## 12 0.0219093636 0.1482251061 0.0842046966 0.174146108 0.20834181
## 13 0.1714238140 0.0407079021 0.0735476533 0.088509042 0.33453983
## 14 0.1714238140 0.0407079021 0.0735476533 0.088509042 0.33453983
## 15 0.1714238140 0.0407079021 0.0735476533 0.088509042 0.33453983
## 16 0.1714238140 0.0407079021 0.0735476533 0.088509042 0.33453983
## 17 0.1714238140 0.0407079021 0.0735476533 0.088509042 0.33453983
## 18 0.1714238140 0.0407079021 0.0735476533 0.088509042 0.33453983
## 19 0.1173109114 0.0030622315 0.0401445005 0.089997061 0.27112753
## 20 0.1173109114 0.0030622315 0.0401445005 0.089997061 0.27112753
## 21 0.1173109114 0.0030622315 0.0401445005 0.089997061 0.27112753
## 22 0.1173109114 0.0030622315 0.0401445005 0.089997061 0.27112753
## 23 0.1173109114 0.0030622315 0.0401445005 0.089997061 0.27112753
## 24 0.1024071432 0.0769168368 0.0483184028 0.059720186 0.17277250
## 25 0.1024071432 0.0769168368 0.0483184028 0.059720186 0.17277250
## 26 0.0259934025 0.0657912974 0.0299582674 0.071289664 0.31902764
## 27 0.0259934025 0.0657912974 0.0299582674 0.071289664 0.31902764
## 28 0.0259934025 0.0657912974 0.0299582674 0.071289664 0.31902764
## 29 0.0749999159 0.0298688661 0.0802394780 0.011002373 0.19810762
## 30 0.0749999159 0.0298688661 0.0802394780 0.011002373 0.19810762
## 31 0.0749999159 0.0298688661 0.0802394780 0.011002373 0.19810762
## 32 0.0749999159 0.0298688661 0.0802394780 0.011002373 0.19810762
## 33 0.0749999159 0.0298688661 0.0802394780 0.011002373 0.19810762
## 34 0.0686617309 0.0682468859 0.0022263662 0.138469585 0.20442691
## 35 0.0686617309 0.0682468859 0.0022263662 0.138469585 0.20442691
## 36 0.0221005290 0.0507449854 0.0408372791 0.188240469 0.30760590
## 37 0.0221005290 0.0507449854 0.0408372791 0.188240469 0.30760590
## 38 0.0221005290 0.0507449854 0.0408372791 0.188240469 0.30760590
## 39 0.0221005290 0.0507449854 0.0408372791 0.188240469 0.30760590
## 40 0.0221005290 0.0507449854 0.0408372791 0.188240469 0.30760590
## 41 0.0221005290 0.0507449854 0.0408372791 0.188240469 0.30760590
## 42 0.0107273363 0.0410987422 0.0142804314 0.006222927 0.20975083
## 43 0.0107273363 0.0410987422 0.0142804314 0.006222927 0.20975083
## 44 0.0107273363 0.0410987422 0.0142804314 0.006222927 0.20975083
## 45 0.0107273363 0.0410987422 0.0142804314 0.006222927 0.20975083
## 46 0.0107273363 0.0410987422 0.0142804314 0.006222927 0.20975083
## 47 0.0441531572 0.0467453683 0.0590319967 0.125445501 0.21896138
## 48 0.0567602191 0.0415848340 0.0073272722 0.063167582 0.24283129
## 49 0.0567602191 0.0415848340 0.0073272722 0.063167582 0.24283129
## 50 0.0567602191 0.0415848340 0.0073272722 0.063167582 0.24283129
## 51 0.0567602191 0.0415848340 0.0073272722 0.063167582 0.24283129
## 52 0.0567602191 0.0415848340 0.0073272722 0.063167582 0.24283129
## 53 0.0567602191 0.0415848340 0.0073272722 0.063167582 0.24283129
## 54 0.0024972843 0.0075130824 0.0049736994 0.003335792 0.19234537
## 55 0.0024972843 0.0075130824 0.0049736994 0.003335792 0.19234537
## 56 0.0024972843 0.0075130824 0.0049736994 0.003335792 0.19234537
## 57 0.0221286297 0.0003510380 0.0183012349 0.196541137 0.30353797
## 58 0.0221286297 0.0003510380 0.0183012349 0.196541137 0.30353797
## 59 0.0221286297 0.0003510380 0.0183012349 0.196541137 0.30353797
## 60 0.0221286297 0.0003510380 0.0183012349 0.196541137 0.30353797
## 61 0.0221286297 0.0003510380 0.0183012349 0.196541137 0.30353797
## 62 0.0221286297 0.0003510380 0.0183012349 0.196541137 0.30353797
## 63 0.0060766879 0.0516606731 0.0438706813 0.240600508 0.24934053
## 64 0.0060766879 0.0516606731 0.0438706813 0.240600508 0.24934053
## 65 0.0060766879 0.0516606731 0.0438706813 0.240600508 0.24934053
## 66 0.0130248599 0.0061462604 0.0174451081 0.499184842 0.43408172
## 67 0.0130248599 0.0061462604 0.0174451081 0.499184842 0.43408172
## 68 0.0149952028 0.0049062759 0.0128898581 0.169637267 0.37908534
## 69 0.0149952028 0.0049062759 0.0128898581 0.169637267 0.37908534
## 70 0.0464724694 0.0337209235 0.1041044407 0.223644824 0.19326069
## 71 0.0464724694 0.0337209235 0.1041044407 0.223644824 0.19326069
## 72 0.0464724694 0.0337209235 0.1041044407 0.223644824 0.19326069
## 73 0.0464724694 0.0337209235 0.1041044407 0.223644824 0.19326069
## 74 0.0593898604 0.1223811804 0.0203254274 0.199458996 0.19214012
## 75 0.0593898604 0.1223811804 0.0203254274 0.199458996 0.19214012
## 76 0.0496071090 0.0089383597 0.0403609406 0.115434957 0.24544185
## 77 0.0021126323 0.0230278434 0.0349774821 0.053886284 0.07554377
## 78 0.0021126323 0.0230278434 0.0349774821 0.053886284 0.07554377
## 79 0.0021126323 0.0230278434 0.0349774821 0.053886284 0.07554377
## 80 0.0021126323 0.0230278434 0.0349774821 0.053886284 0.07554377
## 81 0.0021126323 0.0230278434 0.0349774821 0.053886284 0.07554377
## 82 0.0060684696 0.0496833576 0.0104738107 0.066206917 0.33193787
## 83 0.0060684696 0.0496833576 0.0104738107 0.066206917 0.33193787
## 84 0.0060684696 0.0496833576 0.0104738107 0.066206917 0.33193787
## 85 0.0060684696 0.0496833576 0.0104738107 0.066206917 0.33193787
## 86 0.0060789798 0.0351608840 0.0173068401 0.030300730 0.18549375
## 87 0.0487195955 0.0563907315 0.0268794376 0.067179157 0.16232739
## 88 0.0487195955 0.0563907315 0.0268794376 0.067179157 0.16232739
## 89 0.0361370956 0.0137399114 0.0420543218 0.083904341 0.42084622
## 90 0.0361370956 0.0137399114 0.0420543218 0.083904341 0.42084622
## 91 0.0603435876 0.0676145202 0.0503269821 0.138388430 0.28241639
## 92 0.0603435876 0.0676145202 0.0503269821 0.138388430 0.28241639
## 93 0.0603435876 0.0676145202 0.0503269821 0.138388430 0.28241639
## 94 0.0118989202 0.0179651501 0.0154263804 0.028194556 0.27127334
## 95 0.0118989202 0.0179651501 0.0154263804 0.028194556 0.27127334
## 96 0.0118989202 0.0179651501 0.0154263804 0.028194556 0.27127334
## 97 0.0118989202 0.0179651501 0.0154263804 0.028194556 0.27127334
## 98 0.0080002166 0.0022348445 0.0028403508 0.011806209 0.29124789
## 99 0.0080002166 0.0022348445 0.0028403508 0.011806209 0.29124789
## 100 0.0080002166 0.0022348445 0.0028403508 0.011806209 0.29124789
## 101 0.0080002166 0.0022348445 0.0028403508 0.011806209 0.29124789
## 102 0.0110817786 0.0122285831 0.0440699688 0.338562376 0.16657537
## 103 0.0142076613 0.0255465467 0.0124544157 0.041359915 0.19447820
## 104 0.0142076613 0.0255465467 0.0124544157 0.041359915 0.19447820
## 105 0.0142076613 0.0255465467 0.0124544157 0.041359915 0.19447820
## 106 0.0003342896 0.0001776863 0.0004157795 0.039604058 0.24243762
## 107 0.0003342896 0.0001776863 0.0004157795 0.039604058 0.24243762
## 108 0.0003342896 0.0001776863 0.0004157795 0.039604058 0.24243762
## 109 0.0013134947 0.0016506287 0.0019257089 0.025478398 0.16162714
## 110 0.0013134947 0.0016506287 0.0019257089 0.025478398 0.16162714
## 111 0.0013134947 0.0016506287 0.0019257089 0.025478398 0.16162714
## 112 0.0013134947 0.0016506287 0.0019257089 0.025478398 0.16162714
## 113 0.0013134947 0.0016506287 0.0019257089 0.025478398 0.16162714
## 114 0.0066881719 0.0091020099 0.0068615867 0.106854033 0.16577311
## 115 0.0066881719 0.0091020099 0.0068615867 0.106854033 0.16577311
## 116 0.0066881719 0.0091020099 0.0068615867 0.106854033 0.16577311
## 117 0.0066881719 0.0091020099 0.0068615867 0.106854033 0.16577311
## 118 0.0504752704 0.0315667224 0.0358473085 0.165451275 0.11940338
## 119 0.0504752704 0.0315667224 0.0358473085 0.165451275 0.11940338
## 120 0.0504752704 0.0315667224 0.0358473085 0.165451275 0.11940338
## 121 0.0504752704 0.0315667224 0.0358473085 0.165451275 0.11940338
## 122 0.0504752704 0.0315667224 0.0358473085 0.165451275 0.11940338
## 123 0.0400874487 0.0013240245 0.0406353533 0.008615979 0.27311951
## 124 0.0009407281 0.0010834423 0.0013385373 0.468576361 0.18563851
## 125 0.0009407281 0.0010834423 0.0013385373 0.468576361 0.18563851
## 126 0.0009407281 0.0010834423 0.0013385373 0.468576361 0.18563851
## 127 0.0009407281 0.0010834423 0.0013385373 0.468576361 0.18563851
## 128 0.0009407281 0.0010834423 0.0013385373 0.468576361 0.18563851
## 129 0.0052416704 0.0093143781 0.0209681386 0.180763863 0.15840541
## 130 0.0019420968 0.0811298124 0.1103413532 0.152202191 0.14411385
## 131 0.0019420968 0.0811298124 0.1103413532 0.152202191 0.14411385
## 132 0.0019420968 0.0811298124 0.1103413532 0.152202191 0.14411385
## 133 0.0019420968 0.0811298124 0.1103413532 0.152202191 0.14411385
## 134 0.0019420968 0.0811298124 0.1103413532 0.152202191 0.14411385
## 135 0.0279643868 0.1056375174 0.0675247030 0.160241601 0.24274171
## 136 0.0279643868 0.1056375174 0.0675247030 0.160241601 0.24274171
## 137 0.0279643868 0.1056375174 0.0675247030 0.160241601 0.24274171
## 138 0.0315628102 0.0659828295 0.0187964441 0.015130701 0.28616878
## 139 0.0016382327 0.0036147558 0.0044067512 0.026912518 0.31036738
## 140 0.0016382327 0.0036147558 0.0044067512 0.026912518 0.31036738
## 141 0.0042091625 0.0623715888 0.1616727232 0.209823661 0.23771204
## 142 0.0042091625 0.0623715888 0.1616727232 0.209823661 0.23771204
## 143 0.0308012435 0.0775205038 0.0171061964 0.379395941 0.19997581
## 144 0.0308012435 0.0775205038 0.0171061964 0.379395941 0.19997581
## 145 0.0308012435 0.0775205038 0.0171061964 0.379395941 0.19997581
## 146 0.0026164225 0.0017840092 0.0009158985 0.017421751 0.21294364
## 147 0.0878536049 0.0206508723 0.0763344424 0.013579291 0.30139293
## 148 0.0878536049 0.0206508723 0.0763344424 0.013579291 0.30139293
## 149 0.0878536049 0.0206508723 0.0763344424 0.013579291 0.30139293
## 150 0.0878536049 0.0206508723 0.0763344424 0.013579291 0.30139293
## 151 0.0020844796 0.0047298586 0.0087388050 0.099294761 0.17148767
## 152 0.0020844796 0.0047298586 0.0087388050 0.099294761 0.17148767
## 153 0.0020844796 0.0047298586 0.0087388050 0.099294761 0.17148767
## 154 0.0020844796 0.0047298586 0.0087388050 0.099294761 0.17148767
## 155 0.0063308801 0.0092144203 0.0164759651 0.289586771 0.33355210
## 156 0.0090183856 0.0392075370 0.0141994278 0.023129853 0.30093696
## 157 0.0090183856 0.0392075370 0.0141994278 0.023129853 0.30093696
## 158 0.0090183856 0.0392075370 0.0141994278 0.023129853 0.30093696
## 159 0.0090183856 0.0392075370 0.0141994278 0.023129853 0.30093696
## 160 0.0090183856 0.0392075370 0.0141994278 0.023129853 0.30093696
## 161 0.0090183856 0.0392075370 0.0141994278 0.023129853 0.30093696
## 162 0.0222930784 0.0224613413 0.0383617071 0.166673314 0.31920442
## 163 0.0222930784 0.0224613413 0.0383617071 0.166673314 0.31920442
## 164 0.0321236931 0.0145362517 0.0037742315 0.529736177 0.25561870
## 165 0.0321236931 0.0145362517 0.0037742315 0.529736177 0.25561870
## 166 0.0707777566 0.0801742136 0.0666140261 0.234705486 0.26189644
## 167 0.0707777566 0.0801742136 0.0666140261 0.234705486 0.26189644
## 168 0.0707777566 0.0801742136 0.0666140261 0.234705486 0.26189644
## 169 0.0707777566 0.0801742136 0.0666140261 0.234705486 0.26189644
## 170 0.0707777566 0.0801742136 0.0666140261 0.234705486 0.26189644
## 171 0.0707777566 0.0801742136 0.0666140261 0.234705486 0.26189644
## 172 0.0005315085 0.0006347845 0.0007074545 0.093510454 0.23004535
## 173 0.0005315085 0.0006347845 0.0007074545 0.093510454 0.23004535
## 174 0.0005315085 0.0006347845 0.0007074545 0.093510454 0.23004535
## 175 0.0138049973 0.0230552728 0.0086295474 0.017109955 0.18830985
## 176 0.0138049973 0.0230552728 0.0086295474 0.017109955 0.18830985
## 177 0.0138049973 0.0230552728 0.0086295474 0.017109955 0.18830985
## 178 0.0542821876 0.0658834004 0.0956682764 0.192511143 0.21413002
## 179 0.0542821876 0.0658834004 0.0956682764 0.192511143 0.21413002
## 180 0.0316824850 0.0428115420 0.0384999280 0.131889600 0.17308715
## 181 0.0316824850 0.0428115420 0.0384999280 0.131889600 0.17308715
## 182 0.0549365181 0.0157891470 0.0277318988 0.097399549 0.36653115
## 183 0.0549365181 0.0157891470 0.0277318988 0.097399549 0.36653115
## 184 0.0159742955 0.0075968980 0.0040340112 0.161378655 0.33385840
## 185 0.0159742955 0.0075968980 0.0040340112 0.161378655 0.33385840
## 186 0.0049203581 0.0309548873 0.0502206949 0.089849107 0.17053250
## 187 0.0049203581 0.0309548873 0.0502206949 0.089849107 0.17053250
## 188 0.0049203581 0.0309548873 0.0502206949 0.089849107 0.17053250
## 189 0.0049203581 0.0309548873 0.0502206949 0.089849107 0.17053250
## 190 0.0049203581 0.0309548873 0.0502206949 0.089849107 0.17053250
## 191 0.0049203581 0.0309548873 0.0502206949 0.089849107 0.17053250
## 192 0.0023422414 0.0034467303 0.0063260439 0.012612820 0.23196706
## 193 0.0023422414 0.0034467303 0.0063260439 0.012612820 0.23196706
## 194 0.0023422414 0.0034467303 0.0063260439 0.012612820 0.23196706
## 195 0.0023422414 0.0034467303 0.0063260439 0.012612820 0.23196706
## 196 0.0023422414 0.0034467303 0.0063260439 0.012612820 0.23196706
## 197 0.0029439770 0.0786582119 0.0417886037 0.271710272 0.09874319
## 198 0.0029439770 0.0786582119 0.0417886037 0.271710272 0.09874319
## 199 0.0071113732 0.0342172392 0.0028307947 0.162250347 0.17265373
## 200 0.0071113732 0.0342172392 0.0028307947 0.162250347 0.17265373
## 201 0.0071113732 0.0342172392 0.0028307947 0.162250347 0.17265373
## 202 0.0071113732 0.0342172392 0.0028307947 0.162250347 0.17265373
## 203 0.1252015747 0.0191155529 0.0774956951 0.013079607 0.29084637
## 204 0.1252015747 0.0191155529 0.0774956951 0.013079607 0.29084637
## 205 0.1252015747 0.0191155529 0.0774956951 0.013079607 0.29084637
## 206 0.1252015747 0.0191155529 0.0774956951 0.013079607 0.29084637
## 207 0.0009421062 0.0001991311 0.0005062397 0.197783853 0.24708477
## 208 0.0009421062 0.0001991311 0.0005062397 0.197783853 0.24708477
## 209 0.0230877771 0.0043927675 0.0338673208 0.004270186 0.18338789
## 210 0.0046055736 0.0057213053 0.0032679687 0.079857266 0.29691315
## 211 0.0046055736 0.0057213053 0.0032679687 0.079857266 0.29691315
## 212 0.0046055736 0.0057213053 0.0032679687 0.079857266 0.29691315
## 213 0.0016624646 0.0171952228 0.0022925109 0.352595212 0.11871148
## 214 0.0016624646 0.0171952228 0.0022925109 0.352595212 0.11871148
## 215 0.0016624646 0.0171952228 0.0022925109 0.352595212 0.11871148
## 216 0.0016624646 0.0171952228 0.0022925109 0.352595212 0.11871148
## 217 0.0700415466 0.0649543883 0.0154496150 0.365590887 0.26674800
## 218 0.0700415466 0.0649543883 0.0154496150 0.365590887 0.26674800
## 219 0.0700415466 0.0649543883 0.0154496150 0.365590887 0.26674800
## 220 0.0755281165 0.0910776577 0.1054991820 0.054737063 0.29116925
## 221 0.0755281165 0.0910776577 0.1054991820 0.054737063 0.29116925
## 222 0.0755281165 0.0910776577 0.1054991820 0.054737063 0.29116925
## 223 0.0755281165 0.0910776577 0.1054991820 0.054737063 0.29116925
## 224 0.0755281165 0.0910776577 0.1054991820 0.054737063 0.29116925
## 225 0.0124187759 0.0065825321 0.0273016680 0.197054573 0.09551801
## 226 0.0124187759 0.0065825321 0.0273016680 0.197054573 0.09551801
## 227 0.0287697028 0.0348081277 0.0202574073 0.045937653 0.24186149
## 228 0.0287697028 0.0348081277 0.0202574073 0.045937653 0.24186149
## 229 0.0287697028 0.0348081277 0.0202574073 0.045937653 0.24186149
## 230 0.0287697028 0.0348081277 0.0202574073 0.045937653 0.24186149
## 231 0.0030752788 0.0068926792 0.0055167891 0.197964848 0.20411335
## 232 0.0030752788 0.0068926792 0.0055167891 0.197964848 0.20411335
## 233 0.0030752788 0.0068926792 0.0055167891 0.197964848 0.20411335
## 234 0.0030752788 0.0068926792 0.0055167891 0.197964848 0.20411335
## 235 0.0128836994 0.0145652102 0.0087110352 0.264401789 0.34054367
## 236 0.0128836994 0.0145652102 0.0087110352 0.264401789 0.34054367
## 237 0.0128836994 0.0145652102 0.0087110352 0.264401789 0.34054367
## 238 0.1501177690 0.0172810326 0.1471917200 0.095882011 0.25383583
## 239 0.1501177690 0.0172810326 0.1471917200 0.095882011 0.25383583
## 240 0.1501177690 0.0172810326 0.1471917200 0.095882011 0.25383583
## 241 0.0183494535 0.0054086083 0.0150707904 0.062624924 0.19942065
## 242 0.0494327263 0.0707806614 0.1171202040 0.078395493 0.24788113
## 243 0.0494327263 0.0707806614 0.1171202040 0.078395493 0.24788113
## 244 0.0494327263 0.0707806614 0.1171202040 0.078395493 0.24788113
## 245 0.0494327263 0.0707806614 0.1171202040 0.078395493 0.24788113
## 246 0.0494327263 0.0707806614 0.1171202040 0.078395493 0.24788113
## 247 0.0057392821 0.0014526758 0.0019036352 0.108972582 0.25469019
## 248 0.0057392821 0.0014526758 0.0019036352 0.108972582 0.25469019
## 249 0.0057392821 0.0014526758 0.0019036352 0.108972582 0.25469019
## 250 0.0249447921 0.0091408012 0.0215535330 0.223251951 0.23577872
## 251 0.0249447921 0.0091408012 0.0215535330 0.223251951 0.23577872
## 252 0.0249447921 0.0091408012 0.0215535330 0.223251951 0.23577872
## 253 0.0249447921 0.0091408012 0.0215535330 0.223251951 0.23577872
## 254 0.2345360335 0.0531944592 0.0564060787 0.023454100 0.38439643
## 255 0.0870861053 0.0545775994 0.0396181305 0.005241079 0.23428285
## 256 0.0870861053 0.0545775994 0.0396181305 0.005241079 0.23428285
## 257 0.0870861053 0.0545775994 0.0396181305 0.005241079 0.23428285
## 258 0.0870861053 0.0545775994 0.0396181305 0.005241079 0.23428285
## 259 0.0870861053 0.0545775994 0.0396181305 0.005241079 0.23428285
## 260 0.0057381014 0.0095982764 0.0106058517 0.141888001 0.34537853
## 261 0.0057381014 0.0095982764 0.0106058517 0.141888001 0.34537853
## 262 0.0926465963 0.0365244579 0.1409849298 0.221976689 0.29208170
## 263 0.0159097723 0.0368708500 0.0001344509 0.013043131 0.20218913
## 264 0.0159097723 0.0368708500 0.0001344509 0.013043131 0.20218913
## 265 0.0159097723 0.0368708500 0.0001344509 0.013043131 0.20218913
## 266 0.0019430306 0.0024767520 0.0012230680 0.056851802 0.29263159
## 267 0.0019430306 0.0024767520 0.0012230680 0.056851802 0.29263159
## 268 0.0019430306 0.0024767520 0.0012230680 0.056851802 0.29263159
## 269 0.0019430306 0.0024767520 0.0012230680 0.056851802 0.29263159
## 270 0.0019430306 0.0024767520 0.0012230680 0.056851802 0.29263159
## 271 0.0019430306 0.0024767520 0.0012230680 0.056851802 0.29263159
## 272 0.0748499419 0.0276644131 0.0099238343 0.145512136 0.36408740
## 273 0.0748499419 0.0276644131 0.0099238343 0.145512136 0.36408740
## 274 0.0106861238 0.0001813461 0.0016352155 0.225791981 0.30614431
## 275 0.0106861238 0.0001813461 0.0016352155 0.225791981 0.30614431
## 276 0.0106861238 0.0001813461 0.0016352155 0.225791981 0.30614431
## 277 0.1137220786 0.0277601743 0.0920584516 0.045133557 0.35829654
## 278 0.1137220786 0.0277601743 0.0920584516 0.045133557 0.35829654
## 279 0.1137220786 0.0277601743 0.0920584516 0.045133557 0.35829654
## 280 0.1137220786 0.0277601743 0.0920584516 0.045133557 0.35829654
## 281 0.1137220786 0.0277601743 0.0920584516 0.045133557 0.35829654
## 282 0.0200377619 0.0087570647 0.0242135859 0.008405057 0.26709596
## 283 0.0200377619 0.0087570647 0.0242135859 0.008405057 0.26709596
## 284 0.0200377619 0.0087570647 0.0242135859 0.008405057 0.26709596
## 285 0.0200377619 0.0087570647 0.0242135859 0.008405057 0.26709596
## 286 0.0200377619 0.0087570647 0.0242135859 0.008405057 0.26709596
## 287 0.0391605551 0.0599092866 0.0971675300 0.140044915 0.16947430
## 288 0.0391605551 0.0599092866 0.0971675300 0.140044915 0.16947430
## 289 0.0205303639 0.0227487964 0.0063509762 0.021827593 0.23579058
## 290 0.0205303639 0.0227487964 0.0063509762 0.021827593 0.23579058
## 291 0.0205303639 0.0227487964 0.0063509762 0.021827593 0.23579058
## 292 0.0205303639 0.0227487964 0.0063509762 0.021827593 0.23579058
## 293 0.0205303639 0.0227487964 0.0063509762 0.021827593 0.23579058
## 294 0.0205303639 0.0227487964 0.0063509762 0.021827593 0.23579058
## 295 0.0159065852 0.1033662969 0.1681742328 0.040545575 0.27447848
## 296 0.0159065852 0.1033662969 0.1681742328 0.040545575 0.27447848
## 297 0.0159065852 0.1033662969 0.1681742328 0.040545575 0.27447848
## 298 0.0325372355 0.0195261739 0.0215364452 0.206917100 0.27613279
## 299 0.0325372355 0.0195261739 0.0215364452 0.206917100 0.27613279
## 300 0.0325372355 0.0195261739 0.0215364452 0.206917100 0.27613279
## 301 0.0782564219 0.0690561935 0.0441397108 0.018159618 0.22557428
## 302 0.0782564219 0.0690561935 0.0441397108 0.018159618 0.22557428
## 303 0.0371000165 0.0702324726 0.1484001723 0.111323177 0.11951542
## 304 0.0371000165 0.0702324726 0.1484001723 0.111323177 0.11951542
## 305 0.0371000165 0.0702324726 0.1484001723 0.111323177 0.11951542
## 306 0.0371000165 0.0702324726 0.1484001723 0.111323177 0.11951542
## 307 0.0371000165 0.0702324726 0.1484001723 0.111323177 0.11951542
## 308 0.0144895561 0.0290937921 0.0680078571 0.020467742 0.18779349
## 309 0.0144895561 0.0290937921 0.0680078571 0.020467742 0.18779349
## 310 0.0144895561 0.0290937921 0.0680078571 0.020467742 0.18779349
## 311 0.0951107871 0.3004638226 0.1207813204 0.053443884 0.18481570
## 312 0.0951107871 0.3004638226 0.1207813204 0.053443884 0.18481570
## 313 0.0951107871 0.3004638226 0.1207813204 0.053443884 0.18481570
## 314 0.0951107871 0.3004638226 0.1207813204 0.053443884 0.18481570
## 315 0.0951107871 0.3004638226 0.1207813204 0.053443884 0.18481570
## 316 0.0951107871 0.3004638226 0.1207813204 0.053443884 0.18481570
## 317 0.0048498711 0.0121956112 0.0369425668 0.075593194 0.36991614
## 318 0.0048498711 0.0121956112 0.0369425668 0.075593194 0.36991614
## 319 0.0048498711 0.0121956112 0.0369425668 0.075593194 0.36991614
## 320 0.0870466324 0.0789628210 0.0209538304 0.039934830 0.31925568
## 321 0.0870466324 0.0789628210 0.0209538304 0.039934830 0.31925568
## 322 0.0870466324 0.0789628210 0.0209538304 0.039934830 0.31925568
## 323 0.0870466324 0.0789628210 0.0209538304 0.039934830 0.31925568
## 324 0.0265981031 0.0241621170 0.0171264635 0.054949316 0.19647112
## 325 0.0265981031 0.0241621170 0.0171264635 0.054949316 0.19647112
## 326 0.0265981031 0.0241621170 0.0171264635 0.054949316 0.19647112
## 327 0.0265981031 0.0241621170 0.0171264635 0.054949316 0.19647112
## 328 0.0265981031 0.0241621170 0.0171264635 0.054949316 0.19647112
## LLMWeight_Copilot LLMWeight_Gemini LLMWeight_Inara
## 1 0.2840864 0.24026071 0.26209685
## 2 0.2279423 0.41164790 0.15043926
## 3 0.2279423 0.41164790 0.15043926
## 4 0.2279423 0.41164790 0.15043926
## 5 0.2279423 0.41164790 0.15043926
## 6 0.2279423 0.41164790 0.15043926
## 7 0.2274572 0.34995702 0.15419785
## 8 0.2274572 0.34995702 0.15419785
## 9 0.2277987 0.33785083 0.22600861
## 10 0.2277987 0.33785083 0.22600861
## 11 0.2277987 0.33785083 0.22600861
## 12 0.2277987 0.33785083 0.22600861
## 13 0.2258129 0.13513231 0.30451493
## 14 0.2258129 0.13513231 0.30451493
## 15 0.2258129 0.13513231 0.30451493
## 16 0.2258129 0.13513231 0.30451493
## 17 0.2258129 0.13513231 0.30451493
## 18 0.2258129 0.13513231 0.30451493
## 19 0.1879983 0.11738019 0.42349399
## 20 0.1879983 0.11738019 0.42349399
## 21 0.1879983 0.11738019 0.42349399
## 22 0.1879983 0.11738019 0.42349399
## 23 0.1879983 0.11738019 0.42349399
## 24 0.2060658 0.30123980 0.31992192
## 25 0.2060658 0.30123980 0.31992192
## 26 0.2468989 0.22636850 0.20770500
## 27 0.2468989 0.22636850 0.20770500
## 28 0.2468989 0.22636850 0.20770500
## 29 0.2112495 0.37911105 0.21153181
## 30 0.2112495 0.37911105 0.21153181
## 31 0.2112495 0.37911105 0.21153181
## 32 0.2112495 0.37911105 0.21153181
## 33 0.2112495 0.37911105 0.21153181
## 34 0.2888998 0.21777680 0.28889653
## 35 0.2888998 0.21777680 0.28889653
## 36 0.1979131 0.24075994 0.25372108
## 37 0.1979131 0.24075994 0.25372108
## 38 0.1979131 0.24075994 0.25372108
## 39 0.1979131 0.24075994 0.25372108
## 40 0.1979131 0.24075994 0.25372108
## 41 0.1979131 0.24075994 0.25372108
## 42 0.1490820 0.37286406 0.26830309
## 43 0.1490820 0.37286406 0.26830309
## 44 0.1490820 0.37286406 0.26830309
## 45 0.1490820 0.37286406 0.26830309
## 46 0.1490820 0.37286406 0.26830309
## 47 0.2136511 0.32746497 0.23992259
## 48 0.3449073 0.32111943 0.09114199
## 49 0.3449073 0.32111943 0.09114199
## 50 0.3449073 0.32111943 0.09114199
## 51 0.3449073 0.32111943 0.09114199
## 52 0.3449073 0.32111943 0.09114199
## 53 0.3449073 0.32111943 0.09114199
## 54 0.2918401 0.22510396 0.29071057
## 55 0.2918401 0.22510396 0.29071057
## 56 0.2918401 0.22510396 0.29071057
## 57 0.2869932 0.13990934 0.26955945
## 58 0.2869932 0.13990934 0.26955945
## 59 0.2869932 0.13990934 0.26955945
## 60 0.2869932 0.13990934 0.26955945
## 61 0.2869932 0.13990934 0.26955945
## 62 0.2869932 0.13990934 0.26955945
## 63 0.2240520 0.27608819 0.25051924
## 64 0.2240520 0.27608819 0.25051924
## 65 0.2240520 0.27608819 0.25051924
## 66 0.1666097 0.25725328 0.14205530
## 67 0.1666097 0.25725328 0.14205530
## 68 0.1642415 0.23620744 0.22046573
## 69 0.1642415 0.23620744 0.22046573
## 70 0.3899979 0.23982333 0.17691808
## 71 0.3899979 0.23982333 0.17691808
## 72 0.3899979 0.23982333 0.17691808
## 73 0.3899979 0.23982333 0.17691808
## 74 0.1065891 0.41308706 0.28818371
## 75 0.1065891 0.41308706 0.28818371
## 76 0.1240035 0.30927902 0.32127568
## 77 0.4930947 0.16748057 0.26388093
## 78 0.4930947 0.16748057 0.26388093
## 79 0.4930947 0.16748057 0.26388093
## 80 0.4930947 0.16748057 0.26388093
## 81 0.4930947 0.16748057 0.26388093
## 82 0.2758370 0.24159365 0.15063152
## 83 0.2758370 0.24159365 0.15063152
## 84 0.2758370 0.24159365 0.15063152
## 85 0.2758370 0.24159365 0.15063152
## 86 0.3430656 0.28581979 0.18562088
## 87 0.3023496 0.14745160 0.38787141
## 88 0.3023496 0.14745160 0.38787141
## 89 0.2051075 0.24191909 0.13212721
## 90 0.2051075 0.24191909 0.13212721
## 91 0.2678058 0.21330637 0.23647144
## 92 0.2678058 0.21330637 0.23647144
## 93 0.2678058 0.21330637 0.23647144
## 94 0.2008066 0.33319074 0.19472929
## 95 0.2008066 0.33319074 0.19472929
## 96 0.2008066 0.33319074 0.19472929
## 97 0.2008066 0.33319074 0.19472929
## 98 0.2226830 0.18490190 0.30116725
## 99 0.2226830 0.18490190 0.30116725
## 100 0.2226830 0.18490190 0.30116725
## 101 0.2226830 0.18490190 0.30116725
## 102 0.2706220 0.24559139 0.31721129
## 103 0.2645405 0.38225351 0.15872781
## 104 0.2645405 0.38225351 0.15872781
## 105 0.2645405 0.38225351 0.15872781
## 106 0.2462753 0.34643030 0.16485676
## 107 0.2462753 0.34643030 0.16485676
## 108 0.2462753 0.34643030 0.16485676
## 109 0.4729914 0.21464789 0.15073356
## 110 0.4729914 0.21464789 0.15073356
## 111 0.4729914 0.21464789 0.15073356
## 112 0.4729914 0.21464789 0.15073356
## 113 0.4729914 0.21464789 0.15073356
## 114 0.3678537 0.14308486 0.32328834
## 115 0.3678537 0.14308486 0.32328834
## 116 0.3678537 0.14308486 0.32328834
## 117 0.3678537 0.14308486 0.32328834
## 118 0.2770260 0.41796850 0.18560213
## 119 0.2770260 0.41796850 0.18560213
## 120 0.2770260 0.41796850 0.18560213
## 121 0.2770260 0.41796850 0.18560213
## 122 0.2770260 0.41796850 0.18560213
## 123 0.2641311 0.14395285 0.31879654
## 124 0.2904900 0.33590800 0.18796349
## 125 0.2904900 0.33590800 0.18796349
## 126 0.2904900 0.33590800 0.18796349
## 127 0.2904900 0.33590800 0.18796349
## 128 0.2904900 0.33590800 0.18796349
## 129 0.2818246 0.30645598 0.25331404
## 130 0.2745323 0.43627220 0.14508160
## 131 0.2745323 0.43627220 0.14508160
## 132 0.2745323 0.43627220 0.14508160
## 133 0.2745323 0.43627220 0.14508160
## 134 0.2745323 0.43627220 0.14508160
## 135 0.2282027 0.33829125 0.19076432
## 136 0.2282027 0.33829125 0.19076432
## 137 0.2282027 0.33829125 0.19076432
## 138 0.2798388 0.16465249 0.26933990
## 139 0.1860835 0.18522066 0.31832850
## 140 0.1860835 0.18522066 0.31832850
## 141 0.2919974 0.14222516 0.32806542
## 142 0.2919974 0.14222516 0.32806542
## 143 0.2123324 0.35330873 0.23438302
## 144 0.2123324 0.35330873 0.23438302
## 145 0.2123324 0.35330873 0.23438302
## 146 0.2548794 0.30695053 0.22522640
## 147 0.2126046 0.30153164 0.18447082
## 148 0.2126046 0.30153164 0.18447082
## 149 0.2126046 0.30153164 0.18447082
## 150 0.2126046 0.30153164 0.18447082
## 151 0.3410823 0.16320503 0.32422498
## 152 0.3410823 0.16320503 0.32422498
## 153 0.3410823 0.16320503 0.32422498
## 154 0.3410823 0.16320503 0.32422498
## 155 0.1921781 0.16062446 0.31364530
## 156 0.3083944 0.21161449 0.17905411
## 157 0.3083944 0.21161449 0.17905411
## 158 0.3083944 0.21161449 0.17905411
## 159 0.3083944 0.21161449 0.17905411
## 160 0.3083944 0.21161449 0.17905411
## 161 0.3083944 0.21161449 0.17905411
## 162 0.1571884 0.36437918 0.15922802
## 163 0.1571884 0.36437918 0.15922802
## 164 0.2291539 0.23465972 0.28056765
## 165 0.2291539 0.23465972 0.28056765
## 166 0.2496289 0.31330657 0.17516813
## 167 0.2496289 0.31330657 0.17516813
## 168 0.2496289 0.31330657 0.17516813
## 169 0.2496289 0.31330657 0.17516813
## 170 0.2496289 0.31330657 0.17516813
## 171 0.2496289 0.31330657 0.17516813
## 172 0.1470065 0.41355886 0.20938925
## 173 0.1470065 0.41355886 0.20938925
## 174 0.1470065 0.41355886 0.20938925
## 175 0.4357629 0.27936335 0.09656391
## 176 0.4357629 0.27936335 0.09656391
## 177 0.4357629 0.27936335 0.09656391
## 178 0.2688994 0.25387481 0.26309576
## 179 0.2688994 0.25387481 0.26309576
## 180 0.2948777 0.39024050 0.14179469
## 181 0.2948777 0.39024050 0.14179469
## 182 0.2684663 0.14657878 0.21842380
## 183 0.2684663 0.14657878 0.21842380
## 184 0.2232949 0.19503192 0.24781474
## 185 0.2232949 0.19503192 0.24781474
## 186 0.2814778 0.18662878 0.36136090
## 187 0.2814778 0.18662878 0.36136090
## 188 0.2814778 0.18662878 0.36136090
## 189 0.2814778 0.18662878 0.36136090
## 190 0.2814778 0.18662878 0.36136090
## 191 0.2814778 0.18662878 0.36136090
## 192 0.2810717 0.24341021 0.24355102
## 193 0.2810717 0.24341021 0.24355102
## 194 0.2810717 0.24341021 0.24355102
## 195 0.2810717 0.24341021 0.24355102
## 196 0.2810717 0.24341021 0.24355102
## 197 0.2524277 0.34281883 0.30601026
## 198 0.2524277 0.34281883 0.30601026
## 199 0.1051921 0.49015720 0.23199699
## 200 0.1051921 0.49015720 0.23199699
## 201 0.1051921 0.49015720 0.23199699
## 202 0.1051921 0.49015720 0.23199699
## 203 0.3334780 0.18235132 0.19332426
## 204 0.3334780 0.18235132 0.19332426
## 205 0.3334780 0.18235132 0.19332426
## 206 0.3334780 0.18235132 0.19332426
## 207 0.2184483 0.25201893 0.28244805
## 208 0.2184483 0.25201893 0.28244805
## 209 0.2926948 0.36383508 0.16008222
## 210 0.2572519 0.29266619 0.15316875
## 211 0.2572519 0.29266619 0.15316875
## 212 0.2572519 0.29266619 0.15316875
## 213 0.2144499 0.43728848 0.22955009
## 214 0.2144499 0.43728848 0.22955009
## 215 0.2144499 0.43728848 0.22955009
## 216 0.2144499 0.43728848 0.22955009
## 217 0.1790296 0.28673312 0.26748929
## 218 0.1790296 0.28673312 0.26748929
## 219 0.1790296 0.28673312 0.26748929
## 220 0.3318588 0.19268609 0.18428581
## 221 0.3318588 0.19268609 0.18428581
## 222 0.3318588 0.19268609 0.18428581
## 223 0.3318588 0.19268609 0.18428581
## 224 0.3318588 0.19268609 0.18428581
## 225 0.5401655 0.17044407 0.19387243
## 226 0.5401655 0.17044407 0.19387243
## 227 0.2089540 0.31585363 0.23333091
## 228 0.2089540 0.31585363 0.23333091
## 229 0.2089540 0.31585363 0.23333091
## 230 0.2089540 0.31585363 0.23333091
## 231 0.3226604 0.14061440 0.33261184
## 232 0.3226604 0.14061440 0.33261184
## 233 0.3226604 0.14061440 0.33261184
## 234 0.3226604 0.14061440 0.33261184
## 235 0.2614152 0.20239947 0.19564168
## 236 0.2614152 0.20239947 0.19564168
## 237 0.2614152 0.20239947 0.19564168
## 238 0.2688879 0.12481829 0.35245801
## 239 0.2688879 0.12481829 0.35245801
## 240 0.2688879 0.12481829 0.35245801
## 241 0.2730119 0.22594449 0.30162300
## 242 0.2839626 0.33604119 0.13211506
## 243 0.2839626 0.33604119 0.13211506
## 244 0.2839626 0.33604119 0.13211506
## 245 0.2839626 0.33604119 0.13211506
## 246 0.2839626 0.33604119 0.13211506
## 247 0.2406014 0.33483390 0.16987449
## 248 0.2406014 0.33483390 0.16987449
## 249 0.2406014 0.33483390 0.16987449
## 250 0.2135537 0.31671828 0.23394931
## 251 0.2135537 0.31671828 0.23394931
## 252 0.2135537 0.31671828 0.23394931
## 253 0.2135537 0.31671828 0.23394931
## 254 0.1486664 0.15155654 0.31538063
## 255 0.1375063 0.30019319 0.32801770
## 256 0.1375063 0.30019319 0.32801770
## 257 0.1375063 0.30019319 0.32801770
## 258 0.1375063 0.30019319 0.32801770
## 259 0.1375063 0.30019319 0.32801770
## 260 0.1790694 0.20256719 0.27298490
## 261 0.1790694 0.20256719 0.27298490
## 262 0.2518384 0.13999084 0.31608910
## 263 0.3000754 0.36473382 0.13300169
## 264 0.3000754 0.36473382 0.13300169
## 265 0.3000754 0.36473382 0.13300169
## 266 0.1950439 0.16985299 0.34247150
## 267 0.1950439 0.16985299 0.34247150
## 268 0.1950439 0.16985299 0.34247150
## 269 0.1950439 0.16985299 0.34247150
## 270 0.1950439 0.16985299 0.34247150
## 271 0.1950439 0.16985299 0.34247150
## 272 0.2259426 0.22621726 0.18375271
## 273 0.2259426 0.22621726 0.18375271
## 274 0.3006676 0.07247602 0.32071210
## 275 0.3006676 0.07247602 0.32071210
## 276 0.3006676 0.07247602 0.32071210
## 277 0.2836713 0.10026886 0.25776331
## 278 0.2836713 0.10026886 0.25776331
## 279 0.2836713 0.10026886 0.25776331
## 280 0.2836713 0.10026886 0.25776331
## 281 0.2836713 0.10026886 0.25776331
## 282 0.3367881 0.17512028 0.22099565
## 283 0.3367881 0.17512028 0.22099565
## 284 0.3367881 0.17512028 0.22099565
## 285 0.3367881 0.17512028 0.22099565
## 286 0.3367881 0.17512028 0.22099565
## 287 0.3002150 0.26464830 0.26566235
## 288 0.3002150 0.26464830 0.26566235
## 289 0.1662348 0.23296229 0.36501229
## 290 0.1662348 0.23296229 0.36501229
## 291 0.1662348 0.23296229 0.36501229
## 292 0.1662348 0.23296229 0.36501229
## 293 0.1662348 0.23296229 0.36501229
## 294 0.1662348 0.23296229 0.36501229
## 295 0.2651796 0.27111495 0.18922694
## 296 0.2651796 0.27111495 0.18922694
## 297 0.2651796 0.27111495 0.18922694
## 298 0.1770500 0.26545525 0.28136198
## 299 0.1770500 0.26545525 0.28136198
## 300 0.1770500 0.26545525 0.28136198
## 301 0.1576897 0.21620050 0.40053553
## 302 0.1576897 0.21620050 0.40053553
## 303 0.3128274 0.13006939 0.43758783
## 304 0.3128274 0.13006939 0.43758783
## 305 0.3128274 0.13006939 0.43758783
## 306 0.3128274 0.13006939 0.43758783
## 307 0.3128274 0.13006939 0.43758783
## 308 0.2753718 0.19916068 0.33767408
## 309 0.2753718 0.19916068 0.33767408
## 310 0.2753718 0.19916068 0.33767408
## 311 0.1736504 0.41497243 0.22656148
## 312 0.1736504 0.41497243 0.22656148
## 313 0.1736504 0.41497243 0.22656148
## 314 0.1736504 0.41497243 0.22656148
## 315 0.1736504 0.41497243 0.22656148
## 316 0.1736504 0.41497243 0.22656148
## 317 0.2183330 0.18440206 0.22734879
## 318 0.2183330 0.18440206 0.22734879
## 319 0.2183330 0.18440206 0.22734879
## 320 0.1171281 0.31302625 0.25059000
## 321 0.1171281 0.31302625 0.25059000
## 322 0.1171281 0.31302625 0.25059000
## 323 0.1171281 0.31302625 0.25059000
## 324 0.1705583 0.18337709 0.44959354
## 325 0.1705583 0.18337709 0.44959354
## 326 0.1705583 0.18337709 0.44959354
## 327 0.1705583 0.18337709 0.44959354
## 328 0.1705583 0.18337709 0.4495935412 Convergence Analysis
library(tidyr)
library(purrr)
# Step 1: Create a binary matrix (Runs × COAs) for each Nmax
congruence_scores <- all_runs %>%
distinct() %>%
group_by(MaxCOAs, Run) %>%
summarise(COA_Set = list(unique(COA_ID)), .groups = "drop") %>%
group_by(MaxCOAs) %>%
summarise(
Congruence = {
runs <- COA_Set
n <- length(runs)
if (n < 2) return(NA_real_)
# Compute pairwise Jaccard similarities
scores <- combn(n, 2, function(idx) {
a <- runs[[idx[1]]]
b <- runs[[idx[2]]]
intersect_len <- length(intersect(a, b))
union_len <- length(union(a, b))
if (union_len == 0) return(NA_real_) else return(intersect_len / union_len)
})
mean(scores, na.rm = TRUE)
},
NumRuns = n()
)
# Print congruence results
print(congruence_scores)## # A tibble: 6 × 3
## MaxCOAs Congruence NumRuns
## <int> <dbl> <int>
## 1 1 1 14
## 2 2 1 23
## 3 3 1 21
## 4 4 1 15
## 5 5 0.853 17
## 6 6 0.849 10# Optional: Save for further analysis
write.csv(congruence_scores, "congruence_by_nmax.csv", row.names = FALSE)
6.2 Social Security Cumulative Pay-In