LBB-Classification1
1. OVERVIEW
The dataset turnover_balance.csv contains information on employee turnover within a company. The dataset ‘turnover_balance.csv’ can be used to analyze how the variabel on this data can influence the turnover in the Company. We wants to get a model with a good performance and can be used to determine the contribution of each variable.
The goal is to analyze how various variables influence employee turnover and to develop predictive models that can help determine the contribution of each variable to turnover.
2. DATA PROCESSING
A. Import Libraries
Begin the steps by importing the necessary libraries required for data manipulation, visualization, and analysis. Common libraries include lubridate for date and time data manipulation, tidyr for data wrangling, ggplot2 for static data visualization, GGally for simplifying complex plots, tidyverse for comprehensive data science tools, scales for formatting, glue for string interpolation, ggrepel for avoiding overlapping text labels, lmtest for regression diagnostics, car for regression diagnostics and statistical analysis, caret for predictive modeling, Metrics for evaluating model performance, and MLmetrics for additional machine learning metrics.
# Load necessary libraries
library(lubridate) # for Date and time data manipulation
library(tidyr) # for data wrangling
library(ggplot2) # Static data visualization
library(GGally)
library(tidyverse)
library(scales) # for comma formatting
library(glue) # String interpolation
library(scales) # for comma formatting
library(ggrepel)
library(lmtest)
library(car)
library(caret)
library(Metrics)
library(MLmetrics)
library(dplyr) # for wrangling
library(inspectdf) # for EDA
library(gtools) # for ML model & assumption
library(caret) # for ML model & evaluation
library(readxl)B. Import Dataset
#> Rows: 7,142
#> Columns: 10
#> $ satisfaction_level <dbl> 0.82, 0.79, 0.73, 0.92, 0.69, 0.98, 0.52, 0.51, …
#> $ last_evaluation <dbl> 0.68, 0.67, 0.95, 0.78, 1.00, 0.97, 0.90, 0.73, …
#> $ number_project <int> 3, 5, 3, 3, 5, 3, 4, 4, 3, 3, 4, 2, 5, 5, 5, 5, …
#> $ average_monthly_hours <int> 140, 156, 149, 218, 237, 209, 285, 229, 190, 192…
#> $ time_spend_company <int> 2, 2, 2, 3, 3, 3, 2, 3, 5, 3, 3, 2, 3, 2, 2, 2, …
#> $ Work_accident <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, …
#> $ promotion_last_5years <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ division <chr> "sales", "product_mng", "support", "technical", …
#> $ salary <chr> "low", "low", "low", "low", "high", "low", "low"…
#> $ left <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …The dataset turnover_balance.csv is loaded, and a quick overview of its structure is displayed using glimpse. The dataset turnover_balance.csv comprises information about employee turnover in a company, containing 7,142 observations and 10 variables. The dataset includes the following columns:
-. satisfaction_level: This numerical variable represents the level of satisfaction of an employee, measured on a scale from 0 to 1. -.last_evaluation: This numerical variable indicates the score of the last performance evaluation, also measured on a scale from 0 to 1. -.number_project: This integer variable counts the number of projects the employee is involved in. -.average_monthly_hours: This integer variable records the average number of hours the employee works per month. -.time_spend_company: This integer variable shows the number of years the employee has been with the company. -.Work_accident: This binary integer variable indicates whether the employee has had a work accident (1 for yes, 0 for no). -.promotion_last_5years: This binary integer variable shows whether the employee has been promoted in the last five years (1 for yes, 0 for no). -.division: This categorical variable denotes the department in which the employee works, such as sales, product management, support, or technical. -. salary: This categorical variable represents the salary level of the employee, classified as low, medium, or high. -.left: This binary integer variable indicates whether the employee has left the company (1 for yes, 0 for no).
Data Cleaning
#> [1] FALSEthere is no missing value
C. Data Manipulation
it is important to ensure that the data types of each column are appropriate for the analysis and modeling.
# Convert 'State' to a factor
turnover <- turnover %>%
mutate(
Work_accident = as.factor(Work_accident),
promotion_last_5years = as.factor(promotion_last_5years),
division = as.factor(division),
salary = as.factor(salary),
left = as.factor(left)
) %>%
glimpse()#> Rows: 7,142
#> Columns: 10
#> $ satisfaction_level <dbl> 0.82, 0.79, 0.73, 0.92, 0.69, 0.98, 0.52, 0.51, …
#> $ last_evaluation <dbl> 0.68, 0.67, 0.95, 0.78, 1.00, 0.97, 0.90, 0.73, …
#> $ number_project <int> 3, 5, 3, 3, 5, 3, 4, 4, 3, 3, 4, 2, 5, 5, 5, 5, …
#> $ average_monthly_hours <int> 140, 156, 149, 218, 237, 209, 285, 229, 190, 192…
#> $ time_spend_company <int> 2, 2, 2, 3, 3, 3, 2, 3, 5, 3, 3, 2, 3, 2, 2, 2, …
#> $ Work_accident <fct> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, …
#> $ promotion_last_5years <fct> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ division <fct> sales, product_mng, support, technical, technica…
#> $ salary <fct> low, low, low, low, high, low, low, low, high, l…
#> $ left <fct> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …D. Exploratory Data
We want to investigate the division based on average monthly hours of employee who’s been left.
df_left_agg <-
turnover %>%
filter(left=="1")%>%
group_by(division) %>%
summarize(average_monthly_hours = mean(average_monthly_hours, n.a= TRUE)) %>%
arrange(desc(average_monthly_hours)) %>%
print()#> # A tibble: 10 × 2
#> division average_monthly_hours
#> <fct> <dbl>
#> 1 technical 214.
#> 2 IT 214.
#> 3 RandD 211.
#> 4 product_mng 208.
#> 5 management 207.
#> 6 accounting 207.
#> 7 support 206.
#> 8 sales 205.
#> 9 marketing 201.
#> 10 hr 197.The result of the exploratory data analysis provides insights into the average monthly working hours of employees who have left the company, categorized by their division. The data indicates that employees in divisions with higher average monthly working hours are more likely to leave the company. The technical, IT, and R&D divisions have the highest average monthly working hours among employees who left, suggesting that these divisions might experience more stress or workload, leading to higher turnover rates. By addressing the high working hours and implementing supportive measures, the company can potentially reduce employee turnover and improve overall job satisfaction.
3. LOGISTIC REGRESSION
A. Pre-Processing Data
We will perform pre-processing steps before building the
classification model. Before we build the model, let us take a look at
the proportion of our target variable in the left column
using prop.table(table(data)) function.
#>
#> 0 1
#> 0.5 0.5Explanation of Results: Proportion of Employees who Stayed (left = 0): 0.5 or 50% Proportion of Employees who Left (left = 1): 0.5 or 50% The result indicates that the dataset is balanced with an equal number of employees who stayed and left the company. Specifically:
50% of the employees in the dataset stayed with the company. 50% of the employees in the dataset left the company.
B. Cross Validation
Cross Validation is a method used to split the data into two parts: training data and testing data. The purpose is to use the train data for modeling, while the test data will be used to evaluate the model we have created when faced with unseen data. Additionally, this can be used to assess the performance of the model we have built in handling unseen data.
The data used to train the model is called training data, while The data used to test the model is called testing data.
We will use RNGkind() dan set.seed() in
cross validation
library(rsample)
RNGkind(sample.kind = "Rounding")
set.seed(100)
# binary split : set training data and testing data with porportion 80:20
splitter <- initial_split(data=turnover, prop = 0.8)
# splitting
train <- training(splitter)
test <- testing(splitter)
# observation train and test data
cat(" observation on train data:", nrow(train), "\n")#> observation on train data: 5713#> observation on test data: 1429C. Modelling
we will fit a logistic regression model to our data. Logistic regression is used for modeling binary outcomes, which, in this case, is the left variable. The left variable indicates whether an employee has left the company or not.
Here is the R code to fit the logistic regression model:
model_logistic <- glm(formula = left ~ ., # memprediksi y tanpa dengan menggunakan semua variable sebagai prediktor
data = train, # data latih hasil cross validation
family = "binomial")
summary(model_logistic)#>
#> Call:
#> glm(formula = left ~ ., family = "binomial", data = train)
#>
#> Coefficients:
#> Estimate Std. Error z value Pr(>|z|)
#> (Intercept) -0.9916588 0.2572100 -3.855 0.000116 ***
#> satisfaction_level -4.6637026 0.1554522 -30.001 < 0.0000000000000002 ***
#> last_evaluation 1.3486580 0.2441434 5.524 0.0000000331 ***
#> number_project -0.4619596 0.0345888 -13.356 < 0.0000000000000002 ***
#> average_monthly_hours 0.0046603 0.0008423 5.533 0.0000000316 ***
#> time_spend_company 0.5433006 0.0302083 17.985 < 0.0000000000000002 ***
#> Work_accident1 -1.5683412 0.1248489 -12.562 < 0.0000000000000002 ***
#> promotion_last_5years1 -1.8527726 0.3521320 -5.262 0.0000001428 ***
#> divisionhr 0.1506603 0.1944332 0.775 0.438417
#> divisionIT -0.1697472 0.1801030 -0.943 0.345936
#> divisionmanagement -0.6447231 0.2268468 -2.842 0.004482 **
#> divisionmarketing -0.0871136 0.1933533 -0.451 0.652320
#> divisionproduct_mng -0.3322115 0.1877558 -1.769 0.076830 .
#> divisionRandD -0.5623727 0.2053928 -2.738 0.006181 **
#> divisionsales -0.1007493 0.1501597 -0.671 0.502254
#> divisionsupport 0.0185694 0.1599557 0.116 0.907580
#> divisiontechnical 0.1114474 0.1569055 0.710 0.477528
#> salarylow 2.0031532 0.1716264 11.672 < 0.0000000000000002 ***
#> salarymedium 1.5014787 0.1729044 8.684 < 0.0000000000000002 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> (Dispersion parameter for binomial family taken to be 1)
#>
#> Null deviance: 7919.9 on 5712 degrees of freedom
#> Residual deviance: 5773.6 on 5694 degrees of freedom
#> AIC: 5811.6
#>
#> Number of Fisher Scoring iterations: 5This means the logistic regression model predicts the left variable using all other variables in the dataset (left ~ .), with a binomial family indicating logistic regression.
Interpretation of Key Variables: -.(Intercept): The log odds of left when all predictors are at their reference levels. Here, the estimate is -0.9917. -.satisfaction_level: A highly significant negative effect (-4.6637) on the likelihood of leaving. Higher satisfaction reduces the likelihood of leaving. -.last_evaluation: A positive effect (1.3487) with high significance. Higher last evaluation scores increase the likelihood of leaving. -.number_project: A negative effect (-0.4620), indicating more projects decrease the likelihood of leaving. -.average_monthly_hours: A small but significant positive effect (0.0047), meaning more hours worked slightly increase the likelihood of leaving. -.time_spend_company: A significant positive effect (0.5433), indicating longer tenure increases the likelihood of leaving. -.Work_accident1: A significant negative effect (-1.5683), indicating having a work accident decreases the likelihood of leaving. -.promotion_last_5years1: A significant negative effect (-1.8528), indicating being promoted decreases the likelihood of leaving. -.division variables: Most divisions are not significant compared to the reference category (e.g., division hr has a p-value of 0.4384). However, some divisions like management and RandD show significant negative effects. -. salary variables: Both salarylow (2.0032) and salarymedium (1.5015) have significant positive effects, indicating lower and medium salary levels increase the likelihood of leaving compared to high salary.
Model Statistics: -. Null deviance: 7919.9 on 5712 degrees of freedom. This represents the deviance of the model with only the intercept. -. Residual deviance: 5773.6 on 5694 degrees of freedom. This shows the deviance of the model with all predictors included. -. AIC (Akaike Information Criterion): 5811.6. A lower AIC indicates a better model fit. -. Number of Fisher Scoring iterations: 5. This shows the number of iterations the fitting algorithm took to converge.
Model Fitting Logistic Regression
In this section, we perform stepwise model selection to improve the logistic regression model by removing insignificant predictors. We use the step function to perform backward elimination. The step function starts with the full model (all predictors included) and iteratively removes the least significant predictors to minimize the Akaike Information Criterion (AIC).
#> Start: AIC=5811.64
#> left ~ satisfaction_level + last_evaluation + number_project +
#> average_monthly_hours + time_spend_company + Work_accident +
#> promotion_last_5years + division + salary
#>
#> Df Deviance AIC
#> <none> 5773.6 5811.6
#> - division 9 5809.2 5829.2
#> - average_monthly_hours 1 5804.6 5840.6
#> - last_evaluation 1 5804.6 5840.6
#> - promotion_last_5years 1 5808.0 5844.0
#> - Work_accident 1 5957.2 5993.2
#> - number_project 1 5964.1 6000.1
#> - salary 2 5966.8 6000.8
#> - time_spend_company 1 6154.6 6190.6
#> - satisfaction_level 1 6976.9 7012.9This table shows the AIC for the full model and the AIC if each predictor were removed. None of the predictors are removed in this case as removing any of them would increase the AIC.
#>
#> Call:
#> glm(formula = left ~ satisfaction_level + last_evaluation + number_project +
#> average_monthly_hours + time_spend_company + Work_accident +
#> promotion_last_5years + division + salary, family = "binomial",
#> data = train)
#>
#> Coefficients:
#> Estimate Std. Error z value Pr(>|z|)
#> (Intercept) -0.9916588 0.2572100 -3.855 0.000116 ***
#> satisfaction_level -4.6637026 0.1554522 -30.001 < 0.0000000000000002 ***
#> last_evaluation 1.3486580 0.2441434 5.524 0.0000000331 ***
#> number_project -0.4619596 0.0345888 -13.356 < 0.0000000000000002 ***
#> average_monthly_hours 0.0046603 0.0008423 5.533 0.0000000316 ***
#> time_spend_company 0.5433006 0.0302083 17.985 < 0.0000000000000002 ***
#> Work_accident1 -1.5683412 0.1248489 -12.562 < 0.0000000000000002 ***
#> promotion_last_5years1 -1.8527726 0.3521320 -5.262 0.0000001428 ***
#> divisionhr 0.1506603 0.1944332 0.775 0.438417
#> divisionIT -0.1697472 0.1801030 -0.943 0.345936
#> divisionmanagement -0.6447231 0.2268468 -2.842 0.004482 **
#> divisionmarketing -0.0871136 0.1933533 -0.451 0.652320
#> divisionproduct_mng -0.3322115 0.1877558 -1.769 0.076830 .
#> divisionRandD -0.5623727 0.2053928 -2.738 0.006181 **
#> divisionsales -0.1007493 0.1501597 -0.671 0.502254
#> divisionsupport 0.0185694 0.1599557 0.116 0.907580
#> divisiontechnical 0.1114474 0.1569055 0.710 0.477528
#> salarylow 2.0031532 0.1716264 11.672 < 0.0000000000000002 ***
#> salarymedium 1.5014787 0.1729044 8.684 < 0.0000000000000002 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> (Dispersion parameter for binomial family taken to be 1)
#>
#> Null deviance: 7919.9 on 5712 degrees of freedom
#> Residual deviance: 5773.6 on 5694 degrees of freedom
#> AIC: 5811.6
#>
#> Number of Fisher Scoring iterations: 5The final model is the same as the initial model (model_logistic) because no predictors were removed during the stepwise selection.
The stepwise selection confirmed that all predictors in the initial model contribute to the prediction of employee turnover (left). Significant predictors include satisfaction level, last evaluation, number of projects, average monthly hours, time spent at the company, work accidents, promotions, and salary levels. These factors provide insights into employee retention and can help in developing strategies to reduce turnover.
D. Prediction
In this section, try to predict the test data using model_logistic to generate probability values. as the model shown the same result we can use either model_logistic or model_step to make predictions using the test data that we already have.
Now, let’s return to our model_logistic. In this section, try to predict the test data using model_logistic to generate probability values. Use the predict() function with the parameter type = “response” and save the results in the prob_value object.
test$prob_value <-
predict(object = model_logistic,
newdata = test,
type = "response")
head(test,10)Since the prediction results in logistic regression are probabilities, we need to convert these values into our target categories/classes. Using a threshold of 0.55, try to classify which employees will resign or not. Use the ifelse() function.
E. Evaluation
The next step after making predictions with the model is evaluation, where we also need to evaluate the performance of the model in predicting new (unseen) data. At this stage, create a confusion matrix for the logistic regression model using the actual labels from the test data and the prediction results (pred_value), then set the positive class to “1” (positive = “1”).
# Compute confusion matrix
log_cm <- confusionMatrix(data =as.factor(test$pred_value),
reference = test$left,
positive = "1")
log_cm#> Confusion Matrix and Statistics
#>
#> Reference
#> Prediction 0 1
#> 0 546 171
#> 1 163 549
#>
#> Accuracy : 0.7663
#> 95% CI : (0.7434, 0.788)
#> No Information Rate : 0.5038
#> P-Value [Acc > NIR] : <0.0000000000000002
#>
#> Kappa : 0.5326
#>
#> Mcnemar's Test P-Value : 0.7017
#>
#> Sensitivity : 0.7625
#> Specificity : 0.7701
#> Pos Pred Value : 0.7711
#> Neg Pred Value : 0.7615
#> Prevalence : 0.5038
#> Detection Rate : 0.3842
#> Detection Prevalence : 0.4983
#> Balanced Accuracy : 0.7663
#>
#> 'Positive' Class : 1
#> 3. K-NEAREST NEIGHBOR
A. Pre-Processing Data
In the k-Nearest Neighbor algorithm, we need to perform an additional data pre-processing step. We need to remove categorical variables except for the left variable.
knn_turnover <- turnover %>%
select(-c(Work_accident, promotion_last_5years, division, salary))
knn_turnover %>% head()B. Cross Validation
Separate the predictor variables and the target variable from the train and test data.
library(rsample)
RNGkind(sample.kind = "Rounding")
set.seed(100)
# binary split : set training data and testing data with porportion 80:20
splitter_knn <- initial_split(data=knn_turnover, prop = 0.8)
# splitting
train_knn <- training(splitter_knn)
test_knn <- testing(splitter_knn)
# variabel target `train`
train_y <- train_knn$left
# variabel target `test`
test_y <- test_knn$left
# observation train and test data
cat(" observation on train_x data:", nrow(train), "\n")#> observation on train_x data: 5713#> observation on test_x data: 1429Check again the train_knn data with ‘glimpse’ function.
#> Rows: 5,713
#> Columns: 6
#> $ satisfaction_level <dbl> 0.75, 0.73, 0.10, 0.90, 0.83, 0.69, 0.44, 0.79, …
#> $ last_evaluation <dbl> 0.59, 0.79, 0.87, 0.58, 0.83, 0.90, 0.56, 0.86, …
#> $ number_project <int> 3, 4, 6, 5, 4, 3, 2, 3, 2, 5, 6, 6, 3, 3, 2, 2, …
#> $ average_monthly_hours <int> 117, 157, 250, 260, 224, 185, 145, 139, 158, 253…
#> $ time_spend_company <int> 3, 3, 4, 2, 4, 4, 3, 3, 3, 2, 4, 2, 3, 3, 3, 3, …
#> $ left <fct> 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, …we have to change the target data type to number
#> Rows: 5,713
#> Columns: 6
#> $ satisfaction_level <dbl> 0.75, 0.73, 0.10, 0.90, 0.83, 0.69, 0.44, 0.79, …
#> $ last_evaluation <dbl> 0.59, 0.79, 0.87, 0.58, 0.83, 0.90, 0.56, 0.86, …
#> $ number_project <int> 3, 4, 6, 5, 4, 3, 2, 3, 2, 5, 6, 6, 3, 3, 2, 2, …
#> $ average_monthly_hours <int> 117, 157, 250, 260, 224, 185, 145, 139, 158, 253…
#> $ time_spend_company <int> 3, 3, 4, 2, 4, 4, 3, 3, 3, 2, 4, 2, 3, 3, 3, 3, …
#> $ left <dbl> 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, …#> Rows: 1,429
#> Columns: 6
#> $ satisfaction_level <dbl> 0.92, 0.84, 0.68, 0.74, 0.62, 0.64, 0.28, 0.70, …
#> $ last_evaluation <dbl> 0.78, 0.37, 0.97, 0.85, 0.77, 0.95, 0.37, 0.80, …
#> $ number_project <int> 3, 5, 3, 5, 3, 3, 3, 4, 3, 5, 3, 3, 5, 3, 4, 4, …
#> $ average_monthly_hours <int> 218, 186, 250, 135, 204, 154, 164, 183, 212, 271…
#> $ time_spend_company <int> 3, 2, 3, 2, 4, 4, 4, 2, 2, 4, 3, 3, 6, 5, 3, 3, …
#> $ left <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …Next, check the class proportions in the train_knn data.
#>
#> 0 1
#> 0.5009627 0.4990373C. Scalling
To normalize the train_knn data, please use the scale() function. The purpose of Scaling is to equalizing the range of predictor variables Meanwhile, to normalize the test data, use the same function but with the center and scale attributes obtained from the train_knn data.
library(dplyr)
# prediktor
train_knn_x <- train_knn %>% select(-left)
test_knn_x <- test_knn %>% select(-left)
# target
train_knn_y <- train_knn$left
test_knn_y <- test_knn$leftlibrary(dplyr)
# scale train_x data
train_knn_xs <- scale(train_knn_x)
# scale test_x data
test_knn_xs <- scale(test_knn_x,
center = attr(train_knn_xs, "scaled:center"),
scale = attr(train_knn_xs, "scaled:scale"))
test_knn_xs#> satisfaction_level last_evaluation number_project average_monthly_hours
#> [1,] 1.38517582 0.35879192 -0.5588552 0.269958177
#> [2,] 1.08229535 -1.90049373 0.8161403 -0.319003994
#> [3,] 0.47653441 1.40577795 -0.5588552 0.858920347
#> [4,] 0.70369477 0.74452361 0.8161403 -1.257662452
#> [5,] 0.24937406 0.30368739 -0.5588552 0.012287227
#> [6,] 0.32509418 1.29556889 -0.5588552 -0.907966164
#> [7,] -1.03786794 -1.90049373 -0.5588552 -0.723915486
#> [8,] 0.55225453 0.46900097 0.1286426 -0.374219197
#> [9,] -0.24280670 0.85473267 -0.5588552 0.159527770
#> [10,] -1.56790876 0.41389645 0.8161403 1.245426771
#> [11,] 1.30945571 -0.85350770 -0.5588552 0.306768312
#> [12,] 1.08229535 -0.63308959 -0.5588552 -0.319003994
#> [13,] -1.41646852 -1.12903034 0.8161403 -0.815940825
#> [14,] -1.37860847 0.24858286 -0.5588552 -1.773004351
#> [15,] 0.21151400 -1.18413487 0.1286426 -0.521459740
#> [16,] 0.70369477 -1.12903034 0.1286426 0.785300076
#> [17,] 0.55225453 1.18535984 0.1286426 0.693274736
#> [18,] 0.28723412 0.85473267 -1.2463529 -1.883434758
#> [19,] 0.02221371 -0.19225336 -0.5588552 0.085907498
#> [20,] 0.70369477 0.68941909 -0.5588552 0.656464601
#> [21,] -1.18930817 -0.52288053 0.8161403 -0.079738112
#> [22,] -0.50782711 1.07515078 -0.5588552 0.104312566
#> [23,] 0.40081430 -0.52288053 -1.2463529 -0.815940825
#> [24,] 0.55225453 0.13837381 -0.5588552 0.380388584
#> [25,] 0.89299506 1.29556889 -0.5588552 0.343578448
#> [26,] 0.81727494 0.13837381 0.8161403 0.730084872
#> [27,] 1.53661606 -0.90861223 0.8161403 0.141122702
#> [28,] 0.59011459 -1.01882128 0.8161403 -0.760725621
#> [29,] 1.57447612 -0.19225336 -0.5588552 -0.337409061
#> [30,] 0.96871518 1.51598701 -1.2463529 -0.871156028
#> [31,] 0.06007377 -0.85350770 -0.5588552 0.693274736
#> [32,] 0.74155483 -0.68819411 0.1286426 -0.079738112
#> [33,] 0.85513500 -1.01882128 -0.5588552 -0.944776300
#> [34,] 0.89299506 1.13025531 -0.5588552 0.012287227
#> [35,] 0.55225453 -1.01882128 0.1286426 -0.944776300
#> [36,] 0.47653441 -0.13714883 0.1286426 0.398793651
#> [37,] 1.27159565 1.07515078 -0.5588552 1.116591296
#> [38,] 0.77941488 -0.02693978 1.5036381 -0.650295214
#> [39,] 1.00657524 -1.23923939 0.1286426 -0.429434401
#> [40,] 0.13579388 -0.52288053 -0.5588552 -0.006117841
#> [41,] -1.45432858 0.35879192 -0.5588552 0.656464601
#> [42,] -0.09136647 0.74452361 -0.5588552 0.601249397
#> [43,] 1.38517582 -0.41267147 0.1286426 -0.245383722
#> [44,] 0.59011459 1.40577795 -0.5588552 0.288363244
#> [45,] -0.16708659 0.85473267 -1.2463529 -1.349687792
#> [46,] 1.53661606 -0.63308959 0.8161403 1.208616635
#> [47,] 1.15801547 -0.30246242 0.1286426 -0.226978655
#> [48,] 0.24937406 -1.07392581 1.5036381 0.914135550
#> [49,] 1.57447612 -0.96371675 0.8161403 -0.337409061
#> [50,] 1.61233618 0.52410550 -0.5588552 -0.429434401
#> [51,] 1.68805629 -0.02693978 0.8161403 -0.319003994
#> [52,] 0.59011459 1.02004625 -0.5588552 -1.202447249
#> [53,] 1.15801547 0.13837381 -1.2463529 -0.466244536
#> [54,] 0.59011459 -0.41267147 -0.5588552 1.171806500
#> [55,] 1.27159565 -0.52288053 0.8161403 -0.134953315
#> [56,] 0.09793383 0.79962814 0.1286426 0.987755822
#> [57,] -0.24280670 -1.12903034 -1.2463529 -0.392624265
#> [58,] 0.51439447 0.74452361 0.8161403 0.785300076
#> [59,] 1.19587553 -0.57798506 -0.5588552 -0.760725621
#> [60,] 1.19587553 -0.52288053 0.8161403 -0.116548248
#> [61,] 0.40081430 0.68941909 0.1286426 -0.116548248
#> [62,] -1.30288835 -0.02693978 0.1286426 1.227021703
#> [63,] 1.61233618 -0.08204431 -0.5588552 0.950945686
#> [64,] -0.16708659 -0.68819411 0.1286426 -0.631890147
#> [65,] 0.06007377 1.24046437 -0.5588552 0.490818990
#> [66,] 1.27159565 1.07515078 -0.5588552 0.546034194
#> [67,] 0.02221371 -0.19225336 0.1286426 -0.815940825
#> [68,] 0.77941488 -0.63308959 0.1286426 -0.484649604
#> [69,] -1.56790876 -1.12903034 0.1286426 0.914135550
#> [70,] 0.62797465 -0.02693978 -0.5588552 0.711679804
#> [71,] 0.62797465 -0.90861223 0.1286426 -1.073611774
#> [72,] -0.09136647 -0.63308959 0.8161403 0.803705143
#> [73,] 0.13579388 -1.56986656 -0.5588552 -0.595080011
#> [74,] -0.16708659 -0.74329864 0.1286426 -1.165637113
#> [75,] -1.34074841 -0.85350770 0.8161403 -0.411029333
#> [76,] 0.89299506 -0.52288053 0.8161403 -0.668700282
#> [77,] 1.68805629 0.02816475 0.8161403 -0.171763451
#> [78,] 0.66583471 -0.19225336 -0.5588552 -1.515333402
#> [79,] -0.24280670 0.68941909 0.8161403 -0.190168519
#> [80,] 1.42303588 0.79962814 0.1286426 -1.073611774
#> [81,] 0.09793383 -0.02693978 -0.5588552 0.490818990
#> [82,] -0.16708659 0.90983720 0.8161403 0.490818990
#> [83,] 0.21151400 -1.34944845 -1.2463529 -0.999991503
#> [84,] -0.09136647 0.52410550 -0.5588552 0.417198719
#> [85,] 1.42303588 1.35067342 0.8161403 -1.257662452
#> [86,] 1.42303588 1.35067342 0.1286426 0.361983516
#> [87,] 0.13579388 0.08326928 -0.5588552 -0.576674943
#> [88,] 0.51439447 0.13837381 0.1286426 0.619654465
#> [89,] 0.09793383 1.29556889 0.1286426 -0.558269875
#> [90,] -1.18930817 0.90983720 0.8161403 -0.079738112
#> [91,] 0.24937406 0.96494173 0.8161403 0.730084872
#> [92,] 0.59011459 -1.12903034 -0.5588552 0.822110211
#> [93,] 0.51439447 0.63431456 0.1286426 0.895730483
#> [94,] -1.37860847 -0.46777600 0.1286426 -1.128826978
#> [95,] 1.57447612 -0.57798506 0.1286426 1.079781161
#> [96,] 1.30945571 -0.41267147 0.1286426 -1.184042181
#> [97,] 0.74155483 0.35879192 -1.2463529 1.024565957
#> [98,] 1.19587553 1.57109153 -0.5588552 -1.018396571
#> [99,] 1.61233618 -0.63308959 0.1286426 -0.226978655
#> [100,] 1.46089594 0.46900097 0.1286426 1.153401432
#> [101,] 1.49875600 -0.46777600 -0.5588552 -0.926371232
#> [102,] -0.01564635 -1.01882128 0.1286426 0.196337905
#> [103,] -0.43210700 -0.35756695 -0.5588552 -0.521459740
#> [104,] 0.85513500 -0.96371675 -0.5588552 -0.779130689
#> [105,] -0.05350641 -1.18413487 0.1286426 0.380388584
#> [106,] -1.49218864 -0.13714883 0.1286426 -0.300598926
#> [107,] 0.77941488 -0.79840317 0.8161403 0.950945686
#> [108,] 1.27159565 1.18535984 0.1286426 0.766895008
#> [109,] -0.16708659 -1.79028467 0.8161403 -1.312877656
#> [110,] 1.49875600 1.24046437 -0.5588552 -0.539864807
#> [111,] 0.02221371 -0.68819411 0.8161403 0.932540618
#> [112,] -1.37860847 1.07515078 -0.5588552 1.190211568
#> [113,] -0.20494664 1.24046437 0.8161403 -0.503054672
#> [114,] -0.50782711 -1.51476203 -0.5588552 -0.374219197
#> [115,] -0.28066676 1.13025531 -0.5588552 0.564439262
#> [116,] 1.53661606 0.02816475 -0.5588552 -0.116548248
#> [117,] 1.65019624 1.02004625 0.1286426 -0.484649604
#> [118,] -1.41646852 -0.96371675 0.1286426 -0.705510418
#> [119,] 0.43867436 0.68941909 1.5036381 0.858920347
#> [120,] -1.41646852 -1.79028467 -1.2463529 -0.484649604
#> [121,] -1.15144811 0.46900097 0.8161403 0.619654465
#> [122,] 1.30945571 -0.79840317 0.1286426 -0.319003994
#> [123,] 0.62797465 0.02816475 0.8161403 1.134996364
#> [124,] 0.06007377 -0.68819411 0.1286426 0.858920347
#> [125,] 0.89299506 1.40577795 -0.5588552 1.245426771
#> [126,] 0.81727494 0.63431456 0.1286426 0.509224058
#> [127,] 1.19587553 -0.63308959 0.8161403 -0.705510418
#> [128,] 0.06007377 -0.41267147 -1.2463529 0.049097363
#> [129,] -0.24280670 1.35067342 -1.2463529 0.049097363
#> [130,] 0.47653441 0.41389645 0.8161403 -1.184042181
#> [131,] -1.53004870 0.79962814 -0.5588552 0.012287227
#> [132,] -0.20494664 -0.41267147 0.8161403 -0.153358383
#> [133,] 0.62797465 -0.13714883 -0.5588552 1.227021703
#> [134,] 0.40081430 0.13837381 0.1286426 -0.447839468
#> [135,] -0.16708659 -0.90861223 0.1286426 1.171806500
#> [136,] 0.36295424 0.19347833 -1.2463529 -0.963181367
#> [137,] -0.12922653 0.46900097 -1.2463529 -1.092016842
#> [138,] -0.20494664 0.19347833 0.8161403 0.950945686
#> [139,] 0.47653441 -0.96371675 0.1286426 -1.055206706
#> [140,] 0.74155483 0.96494173 0.8161403 -0.907966164
#> [141,] 1.23373559 -0.46777600 -0.5588552 1.282236907
#> [142,] 1.46089594 -0.90861223 -0.5588552 -0.797535757
#> [143,] -1.07572800 0.74452361 0.8161403 -1.128826978
#> [144,] 0.40081430 0.96494173 -0.5588552 0.711679804
#> [145,] 1.15801547 -0.02693978 -0.5588552 0.582844330
#> [146,] 0.85513500 -1.23923939 -0.5588552 -0.171763451
#> [147,] 0.89299506 1.40577795 0.8161403 1.153401432
#> [148,] 0.28723412 -1.12903034 0.1286426 -0.926371232
#> [149,] 0.70369477 0.30368739 -0.5588552 0.141122702
#> [150,] -0.20494664 0.68941909 -0.5588552 -0.871156028
#> [151,] 0.70369477 1.13025531 0.1286426 0.417198719
#> [152,] 1.30945571 -0.57798506 -0.5588552 -0.337409061
#> [153,] -0.24280670 -0.13714883 0.1286426 1.227021703
#> [154,] 0.40081430 -0.63308959 -0.5588552 -0.447839468
#> [155,] 0.77941488 0.52410550 0.1286426 -0.190168519
#> [156,] 1.08229535 0.52410550 0.1286426 -0.944776300
#> [157,] 0.89299506 -0.85350770 0.1286426 -0.484649604
#> [158,] -1.53004870 -0.08204431 0.1286426 0.306768312
#> [159,] -0.16708659 0.02816475 -0.5588552 -1.018396571
#> [160,] 1.42303588 1.24046437 0.1286426 0.546034194
#> [161,] 0.89299506 -0.96371675 0.1286426 0.748489940
#> [162,] -0.20494664 1.40577795 0.1286426 1.208616635
#> [163,] -1.41646852 -0.96371675 1.5036381 0.104312566
#> [164,] 0.51439447 0.96494173 -0.5588552 0.233148041
#> [165,] 0.40081430 -0.30246242 -0.5588552 0.141122702
#> [166,] -0.20494664 0.57921003 -1.2463529 1.521502788
#> [167,] 0.93085512 0.96494173 -1.2463529 -0.687105350
#> [168,] -0.24280670 1.29556889 -1.2463529 -0.411029333
#> [169,] 0.77941488 -0.41267147 -0.5588552 -0.263788790
#> [170,] 0.40081430 1.46088248 0.1286426 -0.742320553
#> [171,] -0.09136647 -0.41267147 -0.5588552 -1.110421910
#> [172,] -0.24280670 -0.46777600 0.1286426 0.177932838
#> [173,] 0.59011459 1.35067342 0.1286426 -1.331282724
#> [174,] 0.77941488 0.52410550 -0.5588552 0.398793651
#> [175,] 0.85513500 -1.07392581 0.8161403 -0.208573587
#> [176,] 0.13579388 -0.68819411 0.1286426 0.748489940
#> [177,] 0.59011459 -0.96371675 0.1286426 -0.282193858
#> [178,] 0.93085512 -1.01882128 -0.5588552 0.766895008
#> [179,] -0.96214782 -0.24735789 -0.5588552 -0.981586435
#> [180,] 1.00657524 -0.35756695 0.8161403 -0.466244536
#> [181,] 0.13579388 0.85473267 0.1286426 -0.374219197
#> [182,] 1.15801547 0.85473267 -0.5588552 -0.116548248
#> [183,] 1.57447612 -0.35756695 -0.5588552 0.288363244
#> [184,] -0.62140729 0.19347833 1.5036381 -0.337409061
#> [185,] 1.08229535 0.74452361 0.8161403 0.785300076
#> [186,] -0.62140729 -1.84538920 0.1286426 -1.257662452
#> [187,] -1.22716823 1.02004625 0.8161403 0.564439262
#> [188,] 1.30945571 0.08326928 -1.2463529 -0.006117841
#> [189,] -0.20494664 1.57109153 -0.5588552 -0.999991503
#> [190,] -1.49218864 1.18535984 0.8161403 0.122717634
#> [191,] 0.24937406 0.41389645 -0.5588552 1.024565957
#> [192,] 0.85513500 -0.63308959 0.1286426 -1.110421910
#> [193,] 1.42303588 -0.85350770 0.8161403 -1.165637113
#> [194,] 0.77941488 1.02004625 0.8161403 -1.128826978
#> [195,] 0.21151400 -0.85350770 0.1286426 -0.503054672
#> [196,] 0.70369477 0.19347833 0.1286426 -0.631890147
#> [197,] -1.49218864 -0.08204431 1.5036381 0.785300076
#> [198,] -0.01564635 1.02004625 0.1286426 -0.484649604
#> [199,] 0.85513500 -0.68819411 0.8161403 0.601249397
#> [200,] 1.61233618 -0.13714883 -0.5588552 1.300641975
#> [201,] 1.30945571 -0.63308959 -0.5588552 0.950945686
#> [202,] 0.85513500 1.35067342 -1.2463529 -0.539864807
#> [203,] -1.15144811 0.96494173 0.1286426 -0.907966164
#> [204,] 0.62797465 -1.18413487 -0.5588552 0.987755822
#> [205,] 0.93085512 -0.24735789 -0.5588552 -0.466244536
#> [206,] 0.40081430 0.41389645 0.8161403 -1.276067520
#> [207,] 0.13579388 0.19347833 0.1286426 -0.171763451
#> [208,] 0.81727494 0.19347833 1.5036381 0.785300076
#> [209,] 0.66583471 0.90983720 0.8161403 0.546034194
#> [210,] 0.36295424 1.29556889 -1.2463529 -0.429434401
#> [211,] 1.19587553 -1.12903034 0.1286426 -0.558269875
#> [212,] 0.85513500 -1.01882128 1.5036381 -0.650295214
#> [213,] 0.55225453 -1.23923939 0.1286426 -0.558269875
#> [214,] -0.58354723 -1.56986656 -0.5588552 -1.386497927
#> [215,] 1.19587553 1.13025531 -0.5588552 -1.147232046
#> [216,] 0.06007377 -0.74329864 -0.5588552 -1.312877656
#> [217,] -0.09136647 -0.74329864 0.1286426 0.877325415
#> [218,] 0.40081430 0.46900097 0.1286426 -0.374219197
#> [219,] 1.27159565 0.90983720 0.8161403 0.693274736
#> [220,] -0.96214782 -1.79028467 -0.5588552 -0.521459740
#> [221,] 0.17365394 -0.68819411 0.8161403 -1.055206706
#> [222,] 0.62797465 1.18535984 0.1286426 -0.539864807
#> [223,] 0.17365394 -0.63308959 -0.5588552 0.711679804
#> [224,] 1.61233618 -1.01882128 -0.5588552 0.564439262
#> [225,] -1.45432858 -1.29434392 1.5036381 1.227021703
#> [226,] 0.21151400 -1.18413487 0.1286426 1.208616635
#> [227,] -0.24280670 -0.02693978 -0.5588552 0.950945686
#> [228,] 1.04443530 -0.19225336 0.1286426 -0.098143180
#> [229,] -0.96214782 -1.79028467 -0.5588552 -0.190168519
#> [230,] 0.66583471 1.18535984 -0.5588552 0.030692295
#> [231,] -0.28066676 -0.41267147 0.1286426 0.435603787
#> [232,] 1.57447612 0.90983720 0.1286426 -1.184042181
#> [233,] 0.28723412 1.02004625 0.1286426 0.766895008
#> [234,] 0.66583471 0.13837381 0.8161403 -0.079738112
#> [235,] -0.16708659 -1.56986656 -0.5588552 0.012287227
#> [236,] 1.30945571 1.18535984 0.1286426 1.098186229
#> [237,] -0.01564635 1.18535984 0.1286426 0.656464601
#> [238,] 0.81727494 -0.79840317 0.1286426 0.638059533
#> [239,] 1.53661606 1.29556889 -0.5588552 0.601249397
#> [240,] 0.13579388 -0.52288053 0.1286426 0.030692295
#> [241,] 0.32509418 0.02816475 0.1286426 0.932540618
#> [242,] 1.19587553 1.40577795 0.8161403 -0.963181367
#> [243,] 0.74155483 0.79962814 -0.5588552 0.840515279
#> [244,] -1.41646852 0.19347833 -0.5588552 0.858920347
#> [245,] 1.53661606 -1.29434392 -0.5588552 -0.392624265
#> [246,] -1.34074841 0.30368739 1.5036381 0.177932838
#> [247,] 0.02221371 -0.41267147 -0.5588552 0.049097363
#> [248,] 0.43867436 0.63431456 -0.5588552 1.042971025
#> [249,] 1.65019624 -1.07392581 0.1286426 -0.668700282
#> [250,] 0.28723412 -0.57798506 0.8161403 -0.319003994
#> [251,] 0.02221371 1.35067342 -1.2463529 1.208616635
#> [252,] 1.42303588 1.02004625 0.1286426 0.969350754
#> [253,] 0.59011459 0.13837381 0.1286426 0.049097363
#> [254,] 0.81727494 0.96494173 0.1286426 1.208616635
#> [255,] 0.02221371 1.24046437 -0.5588552 0.417198719
#> [256,] 1.00657524 -1.23923939 0.1286426 1.337452110
#> [257,] 0.66583471 0.96494173 -0.5588552 0.417198719
#> [258,] 0.17365394 -0.52288053 -0.5588552 -1.257662452
#> [259,] 1.61233618 -0.35756695 0.1286426 0.233148041
#> [260,] 0.89299506 -0.79840317 0.1286426 0.546034194
#> [261,] 0.40081430 0.68941909 0.8161403 -0.300598926
#> [262,] 1.08229535 -0.19225336 0.1286426 -0.963181367
#> [263,] 0.28723412 1.46088248 0.1286426 -0.797535757
#> [264,] 1.15801547 0.41389645 -0.5588552 0.711679804
#> [265,] 1.23373559 -0.24735789 0.8161403 -1.147232046
#> [266,] -0.05350641 -0.46777600 -0.5588552 0.141122702
#> [267,] 0.06007377 -0.08204431 0.1286426 0.619654465
#> [268,] 1.42303588 -0.57798506 0.8161403 -0.834345893
#> [269,] 0.13579388 -0.79840317 0.8161403 0.987755822
#> [270,] 1.49875600 1.02004625 0.1286426 0.325173380
#> [271,] -0.16708659 -0.74329864 -1.2463529 -0.411029333
#> [272,] 0.24937406 0.79962814 0.1286426 -1.257662452
#> [273,] 1.15801547 -0.46777600 0.1286426 -0.760725621
#> [274,] 1.12015541 1.24046437 0.8161403 0.582844330
#> [275,] 1.27159565 -1.12903034 0.1286426 -0.337409061
#> [276,] 0.02221371 1.57109153 -0.5588552 1.263831839
#> [277,] 0.96871518 0.30368739 -0.5588552 0.012287227
#> [278,] 0.43867436 0.52410550 -0.5588552 0.325173380
#> [279,] 0.85513500 -0.30246242 0.1286426 0.196337905
#> [280,] -1.18930817 1.29556889 -0.5588552 -0.650295214
#> [281,] -0.12922653 -1.45965751 -1.2463529 -1.073611774
#> [282,] -0.58354723 -1.62497109 -0.5588552 -1.055206706
#> [283,] 0.85513500 0.63431456 0.1286426 -0.834345893
#> [284,] 1.27159565 -0.68819411 -0.5588552 0.803705143
#> [285,] -1.53004870 0.35879192 0.8161403 0.950945686
#> [286,] -1.26502829 -1.01882128 0.1286426 0.748489940
#> [287,] 1.46089594 -0.13714883 0.8161403 -1.073611774
#> [288,] 1.65019624 1.40577795 0.1286426 0.085907498
#> [289,] 0.59011459 -0.35756695 0.1286426 0.656464601
#> [290,] 0.28723412 -0.96371675 -0.5588552 -1.073611774
#> [291,] 0.93085512 -0.79840317 -0.5588552 -0.760725621
#> [292,] -0.05350641 0.52410550 -0.5588552 -1.073611774
#> [293,] 1.49875600 -0.96371675 0.1286426 0.582844330
#> [294,] 0.40081430 -1.29434392 -0.5588552 -0.208573587
#> [295,] 0.36295424 0.13837381 0.1286426 0.546034194
#> [296,] 1.34731577 0.24858286 0.8161403 -0.944776300
#> [297,] 0.62797465 -0.52288053 0.1286426 0.895730483
#> [298,] -0.96214782 -0.19225336 -0.5588552 0.472413923
#> [299,] 1.00657524 0.57921003 0.1286426 -0.723915486
#> [300,] 1.57447612 -1.07392581 0.1286426 0.067502431
#> [301,] 1.53661606 -0.68819411 -0.5588552 0.693274736
#> [302,] 0.51439447 0.57921003 0.1286426 -1.220852317
#> [303,] 0.17365394 1.24046437 0.1286426 -0.797535757
#> [304,] -1.18930817 0.35879192 0.8161403 -1.331282724
#> [305,] -1.45432858 0.52410550 0.8161403 1.411072381
#> [306,] 1.61233618 -0.74329864 0.1286426 -1.239257385
#> [307,] 0.02221371 0.90983720 0.1286426 1.282236907
#> [308,] 1.42303588 0.08326928 0.1286426 1.466287585
#> [309,] -1.07572800 -0.41267147 -1.2463529 -0.282193858
#> [310,] -0.12922653 -0.96371675 0.1286426 0.159527770
#> [311,] 0.93085512 -0.19225336 -0.5588552 -0.797535757
#> [312,] -0.69712741 1.02004625 -0.5588552 0.472413923
#> [313,] 1.65019624 0.35879192 0.1286426 -1.165637113
#> [314,] 1.42303588 -1.07392581 -0.5588552 -0.411029333
#> [315,] -1.11358805 -1.56986656 0.1286426 0.214742973
#> [316,] 1.42303588 -0.85350770 -0.5588552 1.153401432
#> [317,] 1.34731577 -0.57798506 0.1286426 -1.257662452
#> [318,] -1.49218864 1.02004625 1.5036381 0.177932838
#> [319,] 1.38517582 -0.35756695 -0.5588552 -0.503054672
#> [320,] 0.74155483 -0.57798506 -0.5588552 1.098186229
#> [321,] 1.30945571 0.13837381 -0.5588552 -0.337409061
#> [322,] -0.88642770 0.13837381 1.5036381 0.030692295
#> [323,] 0.93085512 -0.52288053 -0.5588552 -0.595080011
#> [324,] 1.27159565 -0.24735789 -0.5588552 1.208616635
#> [325,] 0.96871518 1.02004625 0.1286426 -0.705510418
#> [326,] 1.38517582 1.24046437 -1.2463529 0.380388584
#> [327,] 1.42303588 -1.12903034 -0.5588552 -0.134953315
#> [328,] 1.23373559 0.02816475 0.1286426 0.840515279
#> [329,] 1.38517582 -0.63308959 0.8161403 0.601249397
#> [330,] -0.20494664 -0.24735789 -1.2463529 -1.128826978
#> [331,] 0.93085512 -0.63308959 -0.5588552 0.803705143
#> [332,] -0.09136647 1.46088248 -1.2463529 -0.742320553
#> [333,] -0.20494664 -0.24735789 -0.5588552 0.785300076
#> [334,] 0.17365394 0.41389645 0.8161403 0.251553109
#> [335,] 0.81727494 -0.02693978 -1.2463529 0.711679804
#> [336,] 1.23373559 0.96494173 0.8161403 -0.263788790
#> [337,] -0.20494664 -1.29434392 0.1286426 -1.349687792
#> [338,] 0.96871518 -1.18413487 0.8161403 0.030692295
#> [339,] 0.77941488 0.24858286 -0.5588552 -0.116548248
#> [340,] -0.24280670 -0.35756695 0.1286426 0.546034194
#> [341,] 1.46089594 0.68941909 0.8161403 -0.006117841
#> [342,] 0.74155483 -0.46777600 -0.5588552 -1.018396571
#> [343,] 1.00657524 -0.35756695 0.8161403 -0.466244536
#> [344,] -0.46996706 -0.19225336 -0.5588552 -0.116548248
#> [345,] 0.02221371 1.24046437 -0.5588552 -0.907966164
#> [346,] 1.46089594 -0.08204431 -0.5588552 1.245426771
#> [347,] 0.62797465 -0.24735789 0.1286426 -0.208573587
#> [348,] 0.40081430 1.13025531 0.1286426 0.656464601
#> [349,] -1.00000788 0.90983720 1.5036381 -0.374219197
#> [350,] -0.73498747 -0.30246242 0.1286426 -1.957055030
#> [351,] -0.05350641 1.07515078 -1.2463529 -0.871156028
#> [352,] 1.65019624 1.35067342 0.8161403 1.061376093
#> [353,] -0.09136647 0.46900097 -0.5588552 -0.521459740
#> [354,] 1.23373559 0.13837381 0.8161403 0.766895008
#> [355,] 0.89299506 -1.29434392 0.8161403 -0.061333044
#> [356,] 0.24937406 -1.62497109 -1.2463529 -1.460118198
#> [357,] 1.00657524 -0.30246242 0.1286426 0.638059533
#> [358,] 0.32509418 0.02816475 0.1286426 -0.944776300
#> [359,] 0.70369477 0.85473267 -0.5588552 -0.889561096
#> [360,] 0.51439447 0.79962814 0.1286426 0.196337905
#> [361,] 0.81727494 0.08326928 -0.5588552 -0.042927976
#> [362,] 0.36295424 -1.62497109 1.5036381 0.306768312
#> [363,] -0.16708659 -0.46777600 0.8161403 1.042971025
#> [364,] 0.96871518 0.63431456 0.1286426 1.024565957
#> [365,] 1.34731577 -1.01882128 -1.2463529 1.282236907
#> [366,] 1.15801547 0.63431456 0.8161403 0.085907498
#> [367,] 0.81727494 -0.08204431 -0.5588552 -0.889561096
#> [368,] 0.02221371 -1.79028467 0.8161403 1.098186229
#> [369,] 0.36295424 -0.24735789 0.1286426 -1.092016842
#> [370,] 1.19587553 1.24046437 0.1286426 -0.263788790
#> [371,] 0.17365394 -0.52288053 0.8161403 -0.705510418
#> [372,] 1.04443530 0.57921003 -0.5588552 -1.276067520
#> [373,] -1.30288835 0.13837381 0.8161403 -1.147232046
#> [374,] 0.66583471 0.52410550 -0.5588552 -0.650295214
#> [375,] 1.23373559 -0.24735789 0.8161403 1.042971025
#> [376,] 0.06007377 0.08326928 -0.5588552 -1.368092859
#> [377,] 1.61233618 -0.96371675 0.1286426 -0.466244536
#> [378,] 0.40081430 -1.18413487 -0.5588552 0.269958177
#> [379,] 0.77941488 -0.08204431 -0.5588552 -1.239257385
#> [380,] -0.09136647 1.07515078 0.8161403 -0.411029333
#> [381,] 0.43867436 -1.51476203 0.8161403 0.159527770
#> [382,] -0.05350641 1.57109153 -0.5588552 -0.631890147
#> [383,] 1.53661606 0.90983720 -0.5588552 -0.650295214
#> [384,] 0.02221371 -0.68819411 -0.5588552 0.361983516
#> [385,] 1.00657524 0.90983720 0.1286426 -0.999991503
#> [386,] -0.05350641 0.52410550 0.1286426 0.987755822
#> [387,] 0.66583471 -1.18413487 0.1286426 0.380388584
#> [388,] 0.70369477 -0.96371675 -0.5588552 -0.521459740
#> [389,] 1.15801547 1.24046437 -0.5588552 -0.963181367
#> [390,] 0.21151400 0.68941909 0.1286426 1.134996364
#> [391,] 0.51439447 0.68941909 -0.5588552 0.435603787
#> [392,] 0.59011459 -1.95559826 0.1286426 1.374262246
#> [393,] 0.55225453 -0.08204431 -0.5588552 -0.760725621
#> [394,] 0.70369477 1.13025531 0.8161403 0.950945686
#> [395,] 1.46089594 -0.68819411 1.5036381 0.159527770
#> [396,] 0.21151400 0.96494173 -0.5588552 -0.042927976
#> [397,] -0.50782711 -1.18413487 -1.2463529 -0.963181367
#> [398,] -0.20494664 -1.07392581 0.1286426 -0.466244536
#> [399,] -1.30288835 0.85473267 0.1286426 -1.018396571
#> [400,] 0.36295424 1.13025531 0.1286426 -1.294472588
#> [401,] 0.36295424 -1.01882128 0.1286426 -0.797535757
#> [402,] 1.27159565 0.30368739 -0.5588552 -1.092016842
#> [403,] -0.58354723 -0.52288053 0.1286426 -1.404902995
#> [404,] 0.24937406 0.57921003 -0.5588552 0.012287227
#> [405,] -0.12922653 -0.90861223 0.1286426 0.730084872
#> [406,] 1.49875600 -1.18413487 0.1286426 0.711679804
#> [407,] 0.85513500 -1.18413487 0.1286426 0.159527770
#> [408,] 1.42303588 1.02004625 0.8161403 0.122717634
#> [409,] -0.05350641 -0.41267147 -0.5588552 -0.245383722
#> [410,] 0.66583471 0.90983720 0.1286426 0.601249397
#> [411,] 1.12015541 -1.29434392 0.1286426 0.196337905
#> [412,] -0.09136647 -1.07392581 -0.5588552 0.546034194
#> [413,] 0.24937406 0.96494173 -0.5588552 -0.926371232
#> [414,] 0.36295424 0.57921003 0.1286426 -0.134953315
#> [415,] 0.47653441 1.13025531 -0.5588552 0.417198719
#> [416,] 0.77941488 -0.41267147 0.1286426 -1.092016842
#> [417,] -0.96214782 -0.57798506 -0.5588552 -1.202447249
#> [418,] 1.12015541 1.46088248 0.8161403 0.343578448
#> [419,] 0.28723412 -1.23923939 0.1286426 -0.963181367
#> [420,] 0.47653441 -0.35756695 -0.5588552 0.730084872
#> [421,] 0.02221371 1.46088248 0.8161403 -0.595080011
#> [422,] 1.68805629 -0.63308959 0.1286426 1.134996364
#> [423,] -0.65926735 -0.96371675 -1.2463529 -1.680979012
#> [424,] 0.36295424 1.24046437 0.1286426 -0.355814129
#> [425,] 0.17365394 -1.07392581 -0.5588552 -0.374219197
#> [426,] -0.01564635 0.46900097 -0.5588552 -0.208573587
#> [427,] 1.65019624 0.68941909 0.1286426 -1.128826978
#> [428,] 0.28723412 -0.30246242 0.1286426 -0.852750960
#> [429,] -0.01564635 -0.41267147 1.5036381 -1.018396571
#> [430,] 0.85513500 1.40577795 0.1286426 0.325173380
#> [431,] 1.65019624 -0.57798506 0.8161403 -0.134953315
#> [432,] 0.06007377 1.02004625 -0.5588552 -1.092016842
#> [433,] -0.09136647 -1.18413487 0.1286426 -0.337409061
#> [434,] -0.62140729 -1.68007562 1.5036381 -1.625763809
#> [435,] 0.74155483 0.63431456 -0.5588552 -1.055206706
#> [436,] 1.49875600 -0.35756695 -0.5588552 -0.374219197
#> [437,] 1.12015541 -0.63308959 0.1286426 0.987755822
#> [438,] 1.34731577 0.96494173 -1.2463529 0.288363244
#> [439,] 0.81727494 -1.29434392 0.8161403 1.079781161
#> [440,] 0.89299506 -0.96371675 1.5036381 -0.245383722
#> [441,] -0.20494664 0.79962814 -0.5588552 0.914135550
#> [442,] -1.53004870 1.07515078 0.8161403 0.490818990
#> [443,] 1.57447612 -0.41267147 -0.5588552 0.619654465
#> [444,] 1.08229535 0.96494173 0.1286426 -0.300598926
#> [445,] 0.13579388 0.41389645 -0.5588552 0.251553109
#> [446,] 0.81727494 0.85473267 -0.5588552 1.319047042
#> [447,] 0.77941488 -0.74329864 0.8161403 -1.239257385
#> [448,] 0.51439447 0.96494173 -1.2463529 -0.024522908
#> [449,] 1.19587553 1.46088248 -0.5588552 -0.539864807
#> [450,] 0.62797465 -0.08204431 -0.5588552 0.638059533
#> [451,] 1.00657524 -0.02693978 0.8161403 0.085907498
#> [452,] 1.30945571 0.35879192 0.1286426 1.061376093
#> [453,] 0.51439447 0.35879192 0.8161403 1.171806500
#> [454,] 1.49875600 1.29556889 0.1286426 0.012287227
#> [455,] 0.21151400 0.68941909 -0.5588552 0.049097363
#> [456,] -0.73498747 -1.68007562 -0.5588552 -0.668700282
#> [457,] 0.40081430 -0.46777600 0.8161403 1.116591296
#> [458,] 0.21151400 0.96494173 -1.2463529 1.539907856
#> [459,] 1.12015541 -0.63308959 0.8161403 -0.466244536
#> [460,] -0.12922653 0.57921003 0.1286426 -0.098143180
#> [461,] -0.73498747 -1.73518015 -1.2463529 -1.809814487
#> [462,] 1.38517582 -0.19225336 0.1286426 -1.202447249
#> [463,] -1.53004870 0.19347833 -0.5588552 1.024565957
#> [464,] -0.09136647 -1.12903034 -0.5588552 1.300641975
#> [465,] 0.40081430 -1.23923939 0.8161403 0.582844330
#> [466,] 1.04443530 -0.90861223 -0.5588552 1.245426771
#> [467,] 0.51439447 -0.96371675 -0.5588552 -0.723915486
#> [468,] 0.66583471 -0.52288053 0.8161403 -0.319003994
#> [469,] 0.89299506 0.57921003 0.1286426 0.306768312
#> [470,] 1.42303588 0.79962814 0.1286426 -0.631890147
#> [471,] -0.05350641 -0.52288053 -1.2463529 -1.147232046
#> [472,] 0.24937406 0.41389645 0.1286426 0.233148041
#> [473,] 0.55225453 -0.13714883 0.1286426 -0.834345893
#> [474,] 0.51439447 0.13837381 0.8161403 0.435603787
#> [475,] 0.43867436 0.02816475 0.1286426 0.269958177
#> [476,] 1.38517582 1.40577795 0.1286426 -0.042927976
#> [477,] -0.35638688 -0.74329864 0.1286426 -0.595080011
#> [478,] 0.36295424 -1.07392581 -1.2463529 -1.588953673
#> [479,] 0.09793383 0.46900097 0.1286426 -1.662573945
#> [480,] 0.77941488 1.40577795 -0.5588552 1.245426771
#> [481,] 0.17365394 -0.41267147 0.8161403 0.325173380
#> [482,] 0.36295424 1.24046437 0.1286426 -0.355814129
#> [483,] -0.39424694 -1.56986656 0.1286426 0.914135550
#> [484,] 0.51439447 -0.63308959 -0.5588552 -1.184042181
#> [485,] -0.12922653 -0.79840317 -0.5588552 -0.981586435
#> [486,] 0.43867436 0.35879192 -0.5588552 0.582844330
#> [487,] -0.84856764 -0.35756695 -0.5588552 -0.576674943
#> [488,] 1.46089594 -0.41267147 0.8161403 0.803705143
#> [489,] 0.17365394 1.51598701 -0.5588552 -0.300598926
#> [490,] 0.02221371 1.07515078 0.1286426 -0.282193858
#> [491,] 1.30945571 0.85473267 0.1286426 0.509224058
#> [492,] 1.15801547 0.02816475 0.1286426 -0.558269875
#> [493,] 0.13579388 1.07515078 0.1286426 -1.128826978
#> [494,] 0.28723412 -0.90861223 -0.5588552 -0.797535757
#> [495,] 1.12015541 -0.35756695 -0.5588552 -0.153358383
#> [496,] 0.81727494 -0.90861223 -0.5588552 0.251553109
#> [497,] -0.24280670 -1.07392581 0.1286426 -0.779130689
#> [498,] -0.01564635 -0.96371675 -0.5588552 0.914135550
#> [499,] 0.66583471 0.30368739 -0.5588552 0.546034194
#> [500,] 1.61233618 0.19347833 0.8161403 -0.650295214
#> [501,] -0.16708659 1.18535984 0.8161403 0.527629126
#> [502,] -0.50782711 -0.74329864 -1.2463529 -1.165637113
#> [503,] 0.43867436 -1.07392581 -1.2463529 -1.865029691
#> [504,] 1.53661606 -0.02693978 0.1286426 0.122717634
#> [505,] -0.69712741 -0.02693978 -1.2463529 -1.184042181
#> [506,] 0.32509418 1.29556889 -0.5588552 -1.938649962
#> [507,] -0.24280670 -0.35756695 0.1286426 0.546034194
#> [508,] 0.70369477 0.13837381 0.8161403 -0.521459740
#> [509,] 0.62797465 1.29556889 0.1286426 0.490818990
#> [510,] 0.77941488 0.30368739 0.1286426 -0.631890147
#> [511,] 1.61233618 -0.30246242 0.8161403 0.822110211
#> [512,] 0.96871518 1.02004625 0.1286426 1.227021703
#> [513,] 0.24937406 1.46088248 0.1286426 -1.773004351
#> [514,] -1.37860847 0.41389645 0.1286426 0.472413923
#> [515,] 1.12015541 1.35067342 0.8161403 -0.705510418
#> [516,] 1.34731577 0.57921003 -1.2463529 0.693274736
#> [517,] 0.02221371 -0.96371675 0.1286426 -0.226978655
#> [518,] 1.53661606 0.63431456 -0.5588552 0.546034194
#> [519,] 0.47653441 -0.30246242 0.1286426 0.472413923
#> [520,] 0.55225453 0.90983720 0.1286426 -0.429434401
#> [521,] 0.59011459 0.41389645 -0.5588552 -1.276067520
#> [522,] 1.08229535 -0.79840317 0.1286426 0.564439262
#> [523,] -0.12922653 -0.52288053 -0.5588552 1.319047042
#> [524,] 1.04443530 0.68941909 -0.5588552 0.840515279
#> [525,] 0.32509418 -1.12903034 0.1286426 0.803705143
#> [526,] -1.30288835 -0.79840317 0.8161403 0.656464601
#> [527,] -1.30288835 1.18535984 0.1286426 0.730084872
#> [528,] -1.41646852 -0.57798506 0.8161403 -0.539864807
#> [529,] 0.62797465 0.08326928 0.8161403 -0.355814129
#> [530,] 1.00657524 -0.68819411 -0.5588552 0.122717634
#> [531,] 0.70369477 0.90983720 0.8161403 -0.374219197
#> [532,] -0.58354723 0.96494173 -1.2463529 -0.705510418
#> [533,] 1.49875600 -0.19225336 -0.5588552 -0.705510418
#> [534,] 1.23373559 -0.35756695 0.1286426 0.380388584
#> [535,] 0.47653441 -0.30246242 -0.5588552 0.638059533
#> [536,] 0.21151400 0.79962814 -0.5588552 0.638059533
#> [537,] -0.09136647 -0.57798506 0.1286426 -0.392624265
#> [538,] 0.47653441 1.51598701 -0.5588552 -0.815940825
#> [539,] 1.57447612 -0.46777600 0.8161403 -0.742320553
#> [540,] 0.28723412 -0.68819411 0.8161403 0.380388584
#> [541,] 0.96871518 0.79962814 0.8161403 -0.815940825
#> [542,] 0.74155483 -0.68819411 0.8161403 -0.999991503
#> [543,] 0.85513500 0.24858286 -0.5588552 0.638059533
#> [544,] 0.70369477 0.41389645 -0.5588552 1.319047042
#> [545,] 0.93085512 0.35879192 0.8161403 1.153401432
#> [546,] 0.02221371 0.08326928 -0.5588552 0.417198719
#> [547,] 1.19587553 -0.46777600 0.8161403 0.196337905
#> [548,] -1.15144811 -1.68007562 -0.5588552 -1.294472588
#> [549,] 0.09793383 0.41389645 -1.2463529 1.300641975
#> [550,] 0.96871518 -0.30246242 -0.5588552 -0.797535757
#> [551,] 0.93085512 0.08326928 0.8161403 -1.257662452
#> [552,] 1.53661606 1.18535984 -0.5588552 0.638059533
#> [553,] -0.62140729 -1.45965751 -0.5588552 -1.901839826
#> [554,] 1.27159565 1.35067342 -0.5588552 -1.496928334
#> [555,] 1.38517582 -0.52288053 -0.5588552 1.116591296
#> [556,] 0.40081430 0.52410550 0.8161403 -1.257662452
#> [557,] -0.09136647 0.41389645 -0.5588552 0.325173380
#> [558,] 1.57447612 -0.30246242 0.8161403 0.564439262
#> [559,] 0.89299506 -0.68819411 -0.5588552 -1.073611774
#> [560,] 0.43867436 0.68941909 0.1286426 -0.116548248
#> [561,] 0.93085512 -0.52288053 0.8161403 -0.245383722
#> [562,] 0.21151400 1.51598701 0.8161403 -1.938649962
#> [563,] -0.24280670 0.35879192 0.8161403 -1.220852317
#> [564,] 1.57447612 -0.79840317 -0.5588552 -0.723915486
#> [565,] -1.56790876 -1.12903034 0.8161403 -0.558269875
#> [566,] 1.08229535 1.18535984 -0.5588552 -0.815940825
#> [567,] 0.55225453 -0.08204431 -0.5588552 0.380388584
#> [568,] 0.70369477 1.29556889 0.1286426 0.619654465
#> [569,] 0.24937406 0.74452361 0.1286426 0.398793651
#> [570,] -1.18930817 0.85473267 0.8161403 1.190211568
#> [571,] 0.28723412 1.46088248 0.1286426 1.134996364
#> [572,] -0.24280670 0.02816475 0.1286426 0.785300076
#> [573,] -0.09136647 -0.41267147 -1.2463529 -1.736194216
#> [574,] -1.07572800 -0.63308959 1.5036381 0.030692295
#> [575,] -0.54568717 -1.84538920 0.1286426 -1.128826978
#> [576,] -0.12922653 -0.79840317 -0.5588552 1.227021703
#> [577,] -0.28066676 -1.12903034 -0.5588552 -0.042927976
#> [578,] 1.68805629 0.85473267 -0.5588552 -0.705510418
#> [579,] 0.85513500 1.46088248 0.1286426 0.067502431
#> [580,] 0.51439447 -0.19225336 -0.5588552 -1.202447249
#> [581,] 0.32509418 -0.90861223 0.1286426 -0.668700282
#> [582,] -0.24280670 -0.30246242 0.8161403 -0.171763451
#> [583,] -0.81070758 0.85473267 0.1286426 1.466287585
#> [584,] 0.47653441 -0.57798506 -0.5588552 -1.276067520
#> [585,] 1.15801547 0.57921003 0.1286426 1.300641975
#> [586,] -0.05350641 -0.24735789 -1.2463529 -1.368092859
#> [587,] 0.70369477 1.02004625 0.1286426 -0.871156028
#> [588,] 1.27159565 -1.18413487 0.1286426 -1.239257385
#> [589,] -1.37860847 -1.95559826 -0.5588552 -0.668700282
#> [590,] -0.96214782 0.90983720 0.8161403 0.766895008
#> [591,] 1.65019624 -0.74329864 0.1286426 -0.374219197
#> [592,] 0.77941488 0.13837381 -0.5588552 0.380388584
#> [593,] 1.34731577 -0.57798506 -0.5588552 0.950945686
#> [594,] 1.19587553 0.19347833 0.1286426 0.269958177
#> [595,] -0.24280670 0.63431456 -0.5588552 -0.576674943
#> [596,] -1.60576882 1.29556889 0.8161403 -0.999991503
#> [597,] 0.06007377 1.40577795 0.1286426 0.380388584
#> [598,] 0.06007377 -0.85350770 -0.5588552 -0.226978655
#> [599,] 0.06007377 1.46088248 -0.5588552 0.601249397
#> [600,] 0.85513500 -0.57798506 -0.5588552 0.435603787
#> [601,] -1.37860847 -1.29434392 1.5036381 -0.466244536
#> [602,] -0.77284753 -0.96371675 -0.5588552 -1.202447249
#> [603,] -0.24280670 0.90983720 0.1286426 0.748489940
#> [604,] -0.28066676 -0.02693978 -1.2463529 -1.165637113
#> [605,] 1.34731577 -0.85350770 0.1286426 -0.834345893
#> [606,] 0.21151400 0.90983720 0.8161403 -1.276067520
#> [607,] -0.12922653 1.29556889 -0.5588552 -0.595080011
#> [608,] 0.47653441 -1.73518015 -0.5588552 0.177932838
#> [609,] 0.81727494 0.96494173 -1.2463529 0.214742973
#> [610,] 0.28723412 0.63431456 0.1286426 -1.073611774
#> [611,] 0.93085512 0.13837381 -1.2463529 0.030692295
#> [612,] 1.00657524 -0.90861223 -0.5588552 0.067502431
#> [613,] 0.36295424 0.79962814 0.8161403 0.858920347
#> [614,] -0.05350641 -1.40455298 -1.2463529 -1.938649962
#> [615,] -0.20494664 -1.29434392 -0.5588552 -0.742320553
#> [616,] -0.05350641 -1.18413487 0.1286426 -0.797535757
#> [617,] 1.04443530 0.90983720 -0.5588552 0.361983516
#> [618,] 0.24937406 0.08326928 -0.5588552 -1.092016842
#> [619,] 0.21151400 0.79962814 -0.5588552 0.656464601
#> [620,] -0.81070758 -1.23923939 0.1286426 -0.999991503
#> [621,] -1.37860847 -0.57798506 0.1286426 -1.404902995
#> [622,] -0.05350641 -1.07392581 0.1286426 -0.558269875
#> [623,] 1.30945571 -0.85350770 -0.5588552 -0.963181367
#> [624,] 0.24937406 1.40577795 -1.2463529 1.245426771
#> [625,] 0.36295424 -0.30246242 0.8161403 -0.705510418
#> [626,] 0.55225453 -0.19225336 -0.5588552 -0.337409061
#> [627,] 0.74155483 -0.46777600 0.1286426 1.190211568
#> [628,] 1.04443530 0.08326928 0.8161403 -1.239257385
#> [629,] 0.13579388 -0.13714883 0.1286426 0.067502431
#> [630,] -0.81070758 0.57921003 1.5036381 -0.116548248
#> [631,] -1.18930817 -0.41267147 0.8161403 -0.245383722
#> [632,] 1.27159565 -1.79028467 0.8161403 0.269958177
#> [633,] 0.47653441 -0.85350770 -0.5588552 -1.055206706
#> [634,] 0.24937406 -1.23923939 -0.5588552 -0.834345893
#> [635,] 1.08229535 1.29556889 0.8161403 -0.079738112
#> [636,] 0.59011459 -0.52288053 -0.5588552 0.343578448
#> [637,] 0.74155483 1.57109153 -0.5588552 -1.865029691
#> [638,] 0.96871518 1.35067342 -0.5588552 0.417198719
#> [639,] -1.30288835 -0.35756695 0.8161403 0.361983516
#> [640,] 0.70369477 1.29556889 0.8161403 1.153401432
#> [641,] -0.24280670 -0.46777600 -0.5588552 -0.521459740
#> [642,] -1.53004870 -1.01882128 0.1286426 0.030692295
#> [643,] -1.49218864 -0.08204431 0.8161403 0.987755822
#> [644,] 0.40081430 -0.68819411 0.1286426 -0.447839468
#> [645,] 0.13579388 -1.56986656 -0.5588552 -0.558269875
#> [646,] -0.69712741 0.02816475 -0.5588552 -0.374219197
#> [647,] 0.06007377 0.19347833 0.1286426 0.840515279
#> [648,] 0.66583471 0.79962814 0.1286426 -0.134953315
#> [649,] 0.93085512 0.46900097 0.1286426 0.472413923
#> [650,] -1.30288835 -1.56986656 0.8161403 -0.521459740
#> [651,] -0.09136647 0.08326928 0.1286426 0.435603787
#> [652,] 0.28723412 -0.63308959 0.1286426 1.006160889
#> [653,] 1.49875600 0.30368739 0.8161403 -1.184042181
#> [654,] 0.74155483 0.35879192 -1.2463529 0.877325415
#> [655,] -1.56790876 -0.79840317 1.5036381 1.319047042
#> [656,] -0.01564635 0.24858286 0.1286426 0.987755822
#> [657,] 1.30945571 -0.19225336 -0.5588552 -1.257662452
#> [658,] 0.62797465 0.46900097 0.8161403 0.748489940
#> [659,] -0.24280670 -0.68819411 0.1286426 1.134996364
#> [660,] -0.16708659 0.24858286 0.1286426 -1.165637113
#> [661,] 1.46089594 -0.02693978 0.1286426 -0.963181367
#> [662,] 0.13579388 -0.79840317 0.1286426 -0.116548248
#> [663,] 0.17365394 1.29556889 0.1286426 -0.723915486
#> [664,] -0.16708659 -0.41267147 -0.5588552 1.171806500
#> [665,] 0.70369477 0.52410550 0.8161403 1.429477449
#> [666,] 1.12015541 -0.63308959 0.1286426 0.950945686
#> [667,] 1.15801547 1.24046437 -0.5588552 0.159527770
#> [668,] 0.40081430 1.46088248 0.1286426 0.398793651
#> [669,] 1.34731577 -0.63308959 0.8161403 -0.981586435
#> [670,] 0.02221371 -0.08204431 0.1286426 -1.257662452
#> [671,] 1.34731577 0.74452361 0.1286426 -0.006117841
#> [672,] 0.85513500 -0.13714883 0.8161403 0.969350754
#> [673,] -1.18930817 -1.01882128 1.5036381 -0.705510418
#> [674,] 1.00657524 -0.85350770 -1.2463529 0.435603787
#> [675,] 0.85513500 -0.96371675 0.8161403 0.987755822
#> [676,] -0.09136647 -0.57798506 -0.5588552 -1.018396571
#> [677,] 0.36295424 0.19347833 -0.5588552 0.196337905
#> [678,] -1.49218864 -1.07392581 -0.5588552 -1.901839826
#> [679,] 1.04443530 0.46900097 0.1286426 1.300641975
#> [680,] 0.74155483 -0.63308959 0.1286426 -0.319003994
#> [681,] 0.24937406 0.02816475 -0.5588552 -0.999991503
#> [682,] -0.20494664 0.52410550 -0.5588552 -1.018396571
#> [683,] 0.32509418 0.79962814 0.1286426 0.822110211
#> [684,] -0.12922653 -0.30246242 0.8161403 -0.355814129
#> [685,] 1.38517582 0.52410550 0.1286426 0.049097363
#> [686,] 1.34731577 -0.24735789 0.8161403 -1.220852317
#> [687,] 0.40081430 -1.23923939 0.1286426 -0.852750960
#> [688,] 0.40081430 0.35879192 0.1286426 0.969350754
#> [689,] -0.88642770 -1.90049373 -0.5588552 -0.668700282
#> [690,] -1.56790876 0.63431456 0.8161403 -0.926371232
#> [691,] -0.65926735 -0.68819411 0.1286426 1.337452110
#> [692,] -0.24280670 0.13837381 -1.2463529 -0.907966164
#> [693,] 1.38517582 1.18535984 0.1286426 0.398793651
#> [694,] 0.24937406 1.07515078 0.1286426 0.509224058
#> [695,] 0.40081430 0.30368739 0.1286426 -0.282193858
#> [696,] -0.20494664 -1.29434392 0.1286426 1.208616635
#> [697,] 0.47653441 0.96494173 0.8161403 0.269958177
#> [698,] 1.57447612 0.85473267 -0.5588552 0.067502431
#> [699,] -0.31852682 -1.40455298 -1.2463529 -0.944776300
#> [700,] -0.01564635 -0.96371675 -0.5588552 0.546034194
#> [701,] -0.16708659 0.41389645 -0.5588552 -1.220852317
#> [702,] 0.43867436 -1.51476203 0.1286426 -0.171763451
#> [703,] -0.20494664 0.90983720 0.1286426 1.319047042
#> [704,] -0.12922653 -1.34944845 -0.5588552 -1.754599284
#> [705,] -0.92428776 -1.12903034 -1.2463529 -1.055206706
#> [706,] 0.74155483 -0.02693978 0.1286426 0.030692295
#> [707,] 1.68805629 0.90983720 1.5036381 -0.042927976
#> [708,] 0.70369477 -1.18413487 0.1286426 0.233148041
#> [709,] 0.74155483 -1.07392581 -0.5588552 1.042971025
#> [710,] -1.75720905 1.35067342 2.1911358 1.300641975
#> [711,] 0.66583471 1.57109153 0.1286426 1.190211568
#> [712,] -1.07572800 -0.85350770 -0.5588552 1.797578806
#> [713,] 1.12015541 1.46088248 0.8161403 0.822110211
#> [714,] -0.73498747 -1.29434392 -1.2463529 -0.815940825
#> [715,] -0.62140729 -0.79840317 -1.2463529 -0.834345893
#> [716,] 0.96871518 1.40577795 0.8161403 0.730084872
#> [717,] -1.71934900 1.18535984 1.5036381 0.914135550
#> [718,] 1.08229535 0.85473267 0.1286426 0.785300076
#> [719,] -1.75720905 0.46900097 2.1911358 1.466287585
#> [720,] 1.30945571 1.57109153 0.8161403 0.527629126
#> [721,] 0.66583471 0.96494173 0.8161403 0.601249397
#> [722,] -0.43210700 -0.79840317 -1.2463529 -1.018396571
#> [723,] -1.75720905 0.85473267 -0.5588552 0.196337905
#> [724,] -1.68148894 0.46900097 2.1911358 0.730084872
#> [725,] -0.69712741 -1.40455298 -1.2463529 -0.926371232
#> [726,] -1.71934900 1.40577795 1.5036381 1.447882517
#> [727,] -0.65926735 -1.23923939 -1.2463529 -0.963181367
#> [728,] -1.68148894 1.07515078 2.1911358 1.539907856
#> [729,] 0.66583471 1.40577795 0.8161403 0.251553109
#> [730,] -0.62140729 -1.01882128 -1.2463529 -1.404902995
#> [731,] 0.93085512 0.85473267 0.8161403 0.674869669
#> [732,] -1.56790876 -0.52288053 0.1286426 -0.834345893
#> [733,] -0.73498747 -1.29434392 -1.2463529 -0.834345893
#> [734,] 0.70369477 1.51598701 -1.2463529 1.355857178
#> [735,] -1.71934900 1.18535984 1.5036381 1.576717992
#> [736,] 1.34731577 1.29556889 0.8161403 0.693274736
#> [737,] -0.43210700 -1.07392581 -1.2463529 -0.999991503
#> [738,] -0.46996706 -1.29434392 -1.2463529 -0.926371232
#> [739,] -0.73498747 -0.85350770 -1.2463529 -1.220852317
#> [740,] 1.12015541 1.46088248 0.8161403 0.822110211
#> [741,] 1.27159565 1.40577795 0.1286426 1.116591296
#> [742,] -1.68148894 1.29556889 1.5036381 1.392667314
#> [743,] -1.75720905 1.02004625 1.5036381 1.539907856
#> [744,] -1.71934900 0.30368739 0.8161403 1.337452110
#> [745,] -0.62140729 -1.07392581 -1.2463529 -1.276067520
#> [746,] -1.75720905 -0.52288053 1.5036381 1.668743331
#> [747,] 1.00657524 1.51598701 0.1286426 1.098186229
#> [748,] -0.65926735 -1.18413487 -1.2463529 -1.165637113
#> [749,] 0.77941488 1.46088248 0.8161403 0.711679804
#> [750,] -0.39424694 -0.79840317 -1.2463529 -0.963181367
#> [751,] -0.46996706 -0.85350770 -1.2463529 -1.368092859
#> [752,] 1.23373559 0.90983720 0.8161403 0.822110211
#> [753,] 0.81727494 1.18535984 0.1286426 0.509224058
#> [754,] -1.71934900 1.07515078 2.1911358 1.723958534
#> [755,] -0.62140729 -1.23923939 -1.2463529 -1.404902995
#> [756,] -0.50782711 -1.01882128 -1.2463529 -1.128826978
#> [757,] -0.58354723 -1.18413487 -1.2463529 -1.147232046
#> [758,] 1.00657524 1.46088248 0.1286426 0.546034194
#> [759,] -1.68148894 0.35879192 2.1911358 0.822110211
#> [760,] -0.58354723 -1.23923939 -1.2463529 -0.889561096
#> [761,] -0.58354723 -1.34944845 -1.2463529 -0.963181367
#> [762,] 0.70369477 0.96494173 0.1286426 1.171806500
#> [763,] 0.85513500 1.18535984 0.1286426 0.398793651
#> [764,] -1.75720905 0.68941909 2.1911358 1.908009213
#> [765,] -1.64362888 1.57109153 -0.5588552 1.374262246
#> [766,] -0.39424694 -1.07392581 -1.2463529 -1.110421910
#> [767,] -0.43210700 -1.01882128 -1.2463529 -1.036801639
#> [768,] 0.74155483 1.51598701 0.8161403 0.325173380
#> [769,] 0.74155483 0.74452361 0.8161403 0.674869669
#> [770,] 0.85513500 -0.30246242 -0.5588552 -0.723915486
#> [771,] -0.46996706 -1.45965751 -1.2463529 -1.257662452
#> [772,] -1.68148894 1.40577795 1.5036381 1.963224416
#> [773,] -1.68148894 1.02004625 1.5036381 0.932540618
#> [774,] -1.68148894 0.85473267 1.5036381 0.950945686
#> [775,] -0.69712741 -0.90861223 -1.2463529 -0.944776300
#> [776,] -0.62140729 -1.45965751 -1.2463529 -1.165637113
#> [777,] 1.27159565 0.63431456 0.8161403 -1.349687792
#> [778,] -0.46996706 -1.29434392 -1.2463529 -0.852750960
#> [779,] -0.62140729 -1.12903034 -1.2463529 -1.220852317
#> [780,] 1.19587553 1.07515078 0.8161403 0.454008855
#> [781,] -0.35638688 -0.79840317 -1.2463529 -1.184042181
#> [782,] -1.53004870 -0.90861223 1.5036381 -1.184042181
#> [783,] -1.68148894 0.79962814 1.5036381 1.926414280
#> [784,] -0.46996706 -1.34944845 -1.2463529 -0.834345893
#> [785,] -1.68148894 0.74452361 2.1911358 1.815983874
#> [786,] -0.39424694 -0.85350770 -1.2463529 -0.907966164
#> [787,] 1.04443530 0.74452361 0.8161403 0.619654465
#> [788,] -0.54568717 -1.07392581 -1.2463529 -1.036801639
#> [789,] -0.62140729 -1.18413487 -1.2463529 -1.404902995
#> [790,] 0.77941488 0.85473267 0.8161403 0.766895008
#> [791,] -0.58354723 -1.01882128 -1.2463529 -0.834345893
#> [792,] -0.43210700 -1.01882128 -1.2463529 -0.889561096
#> [793,] -1.71934900 0.63431456 1.5036381 1.245426771
#> [794,] -1.71934900 0.52410550 1.5036381 1.595123060
#> [795,] 1.08229535 1.57109153 0.8161403 0.711679804
#> [796,] 0.70369477 1.57109153 0.8161403 0.343578448
#> [797,] -0.69712741 -1.12903034 -1.2463529 -1.312877656
#> [798,] -0.58354723 -1.12903034 -1.2463529 -1.184042181
#> [799,] -0.46996706 -1.29434392 -1.2463529 -1.092016842
#> [800,] -1.34074841 1.02004625 1.5036381 -1.202447249
#> [801,] 1.30945571 1.13025531 0.8161403 0.766895008
#> [802,] -1.71934900 0.74452361 1.5036381 1.723958534
#> [803,] -0.73498747 -1.07392581 -1.2463529 -1.110421910
#> [804,] 0.62797465 1.57109153 0.1286426 -0.631890147
#> [805,] 1.12015541 0.57921003 0.8161403 1.116591296
#> [806,] 0.96871518 0.63431456 0.8161403 1.208616635
#> [807,] -0.50782711 -1.29434392 -1.2463529 -1.165637113
#> [808,] -0.35638688 -1.18413487 -1.2463529 -0.852750960
#> [809,] 1.27159565 0.79962814 0.8161403 1.319047042
#> [810,] -0.58354723 -0.90861223 -1.2463529 -0.981586435
#> [811,] -1.71934900 1.35067342 2.1911358 0.950945686
#> [812,] -1.71934900 0.85473267 2.1911358 0.877325415
#> [813,] -1.71934900 0.46900097 1.5036381 1.116591296
#> [814,] 1.38517582 0.85473267 0.1286426 0.417198719
#> [815,] 0.77941488 0.90983720 0.1286426 0.049097363
#> [816,] -0.43210700 -0.85350770 -1.2463529 -1.404902995
#> [817,] 1.19587553 1.57109153 0.8161403 1.061376093
#> [818,] 0.66583471 1.18535984 0.8161403 -0.760725621
#> [819,] 0.70369477 1.07515078 0.1286426 0.527629126
#> [820,] -0.73498747 -1.07392581 -1.2463529 -1.036801639
#> [821,] 1.08229535 1.13025531 0.1286426 0.564439262
#> [822,] -1.71934900 1.35067342 1.5036381 1.631933195
#> [823,] -1.71934900 1.24046437 2.1911358 1.116591296
#> [824,] -0.43210700 -1.12903034 -1.2463529 -1.276067520
#> [825,] -0.73498747 0.35879192 -1.2463529 -0.963181367
#> [826,] -1.71934900 0.52410550 2.1911358 0.748489940
#> [827,] -1.71934900 1.18535984 1.5036381 1.742363602
#> [828,] 0.70369477 1.51598701 -1.2463529 1.355857178
#> [829,] -0.43210700 -1.40455298 -1.2463529 -1.110421910
#> [830,] -1.71934900 1.18535984 2.1911358 1.871199077
#> [831,] 0.17365394 1.13025531 -1.2463529 1.006160889
#> [832,] -0.54568717 -1.01882128 -1.2463529 -0.852750960
#> [833,] -1.68148894 1.07515078 0.8161403 1.613528128
#> [834,] -1.68148894 1.02004625 2.1911358 0.803705143
#> [835,] -0.58354723 -0.85350770 -1.2463529 -1.331282724
#> [836,] -1.71934900 0.63431456 1.5036381 1.687148399
#> [837,] -1.68148894 0.74452361 1.5036381 1.760768670
#> [838,] 0.70369477 1.51598701 0.1286426 0.546034194
#> [839,] 0.62797465 0.68941909 0.8161403 0.987755822
#> [840,] -0.92428776 -0.52288053 1.5036381 -1.257662452
#> [841,] -1.71934900 1.29556889 0.8161403 1.521502788
#> [842,] -1.53004870 -0.46777600 2.1911358 0.472413923
#> [843,] -1.71934900 1.40577795 2.1911358 0.932540618
#> [844,] -0.73498747 -1.29434392 -1.2463529 -0.944776300
#> [845,] -0.54568717 -0.96371675 -1.2463529 -1.073611774
#> [846,] 0.77941488 1.07515078 0.1286426 0.288363244
#> [847,] -0.35638688 -1.18413487 -1.2463529 -1.147232046
#> [848,] -1.68148894 0.63431456 1.5036381 0.748489940
#> [849,] 0.62797465 0.57921003 0.8161403 1.208616635
#> [850,] -1.71934900 0.63431456 1.5036381 1.374262246
#> [851,] -0.50782711 -1.23923939 -1.2463529 -1.073611774
#> [852,] 1.19587553 1.24046437 0.1286426 1.042971025
#> [853,] -0.50782711 -1.40455298 -1.2463529 -0.981586435
#> [854,] -1.71934900 1.29556889 2.1911358 1.576717992
#> [855,] -0.43210700 -0.90861223 -1.2463529 -1.220852317
#> [856,] -0.46996706 -0.90861223 -1.2463529 -0.815940825
#> [857,] -0.54568717 -1.40455298 -1.2463529 -0.797535757
#> [858,] -1.71934900 0.85473267 1.5036381 1.908009213
#> [859,] -1.71934900 1.29556889 1.5036381 0.748489940
#> [860,] 0.70369477 0.57921003 0.1286426 0.656464601
#> [861,] 1.30945571 1.07515078 0.1286426 1.208616635
#> [862,] -0.43210700 -0.90861223 -1.2463529 -1.239257385
#> [863,] 0.96871518 1.02004625 0.1286426 0.417198719
#> [864,] 1.12015541 0.74452361 0.1286426 0.803705143
#> [865,] -1.68148894 0.35879192 1.5036381 1.834388941
#> [866,] 1.08229535 1.24046437 0.8161403 0.343578448
#> [867,] -1.68148894 1.02004625 2.1911358 0.803705143
#> [868,] -0.35638688 -0.96371675 -1.2463529 -1.110421910
#> [869,] 0.70369477 0.57921003 0.1286426 0.656464601
#> [870,] -0.50782711 -0.79840317 -1.2463529 -0.907966164
#> [871,] 0.70369477 0.96494173 0.8161403 0.472413923
#> [872,] -0.46996706 -1.01882128 -1.2463529 -1.239257385
#> [873,] -0.46996706 -1.34944845 -1.2463529 -1.386497927
#> [874,] -0.58354723 -1.29434392 -1.2463529 -1.202447249
#> [875,] -0.28066676 1.18535984 -0.5588552 0.288363244
#> [876,] 1.04443530 1.13025531 0.8161403 1.171806500
#> [877,] -0.54568717 -0.96371675 -1.2463529 -0.926371232
#> [878,] -1.75720905 0.57921003 1.5036381 0.858920347
#> [879,] -0.50782711 -1.01882128 -1.2463529 -1.312877656
#> [880,] -1.68148894 0.46900097 1.5036381 1.852794009
#> [881,] -1.71934900 1.02004625 2.1911358 1.595123060
#> [882,] 1.00657524 1.24046437 0.8161403 0.527629126
#> [883,] -0.69712741 -1.29434392 -1.2463529 -1.220852317
#> [884,] -1.71934900 0.79962814 2.1911358 1.061376093
#> [885,] -0.46996706 -1.45965751 -1.2463529 -1.257662452
#> [886,] 1.27159565 0.79962814 0.8161403 1.319047042
#> [887,] 1.30945571 0.63431456 0.1286426 1.153401432
#> [888,] -1.71934900 0.52410550 1.5036381 1.190211568
#> [889,] 0.85513500 0.52410550 0.1286426 0.914135550
#> [890,] 0.96871518 1.46088248 0.8161403 0.766895008
#> [891,] -1.75720905 1.46088248 1.5036381 1.245426771
#> [892,] -0.69712741 -1.34944845 -1.2463529 -1.147232046
#> [893,] -0.46996706 -1.29434392 -1.2463529 -1.257662452
#> [894,] -1.68148894 1.29556889 2.1911358 1.779173738
#> [895,] -0.69712741 -1.45965751 -1.2463529 -0.963181367
#> [896,] -0.69712741 -1.12903034 -1.2463529 -1.404902995
#> [897,] -0.73498747 -0.85350770 -1.2463529 -1.312877656
#> [898,] -1.75720905 1.40577795 2.1911358 0.932540618
#> [899,] -0.69712741 -0.79840317 -1.2463529 -1.294472588
#> [900,] 1.30945571 1.46088248 0.8161403 0.766895008
#> [901,] -1.68148894 0.79962814 1.5036381 1.282236907
#> [902,] -1.68148894 1.24046437 2.1911358 0.950945686
#> [903,] 0.81727494 1.57109153 0.1286426 0.527629126
#> [904,] -0.46996706 -1.07392581 -1.2463529 -1.036801639
#> [905,] -0.54568717 -1.40455298 -1.2463529 -0.981586435
#> [906,] -0.50782711 -1.07392581 -1.2463529 -1.276067520
#> [907,] -1.71934900 1.40577795 1.5036381 1.908009213
#> [908,] -0.50782711 -0.85350770 -1.2463529 -1.110421910
#> [909,] 0.85513500 0.85473267 0.1286426 0.454008855
#> [910,] -0.43210700 -1.45965751 -1.2463529 -1.312877656
#> [911,] 0.66583471 1.40577795 0.8161403 0.582844330
#> [912,] -1.71934900 1.18535984 1.5036381 0.914135550
#> [913,] -0.46996706 -0.90861223 -1.2463529 -1.349687792
#> [914,] -0.58354723 -1.40455298 -1.2463529 -1.386497927
#> [915,] -0.39424694 -0.96371675 -1.2463529 -1.128826978
#> [916,] -0.73498747 -0.79840317 -1.2463529 -1.092016842
#> [917,] 0.85513500 0.79962814 0.8161403 1.300641975
#> [918,] -0.50782711 -1.29434392 -1.2463529 -1.368092859
#> [919,] 0.40081430 1.18535984 0.8161403 0.914135550
#> [920,] 1.00657524 0.52410550 0.1286426 0.546034194
#> [921,] 1.04443530 1.29556889 0.1286426 0.877325415
#> [922,] 0.93085512 1.29556889 -0.5588552 -1.055206706
#> [923,] -0.54568717 -1.34944845 -1.2463529 -1.073611774
#> [924,] -0.58354723 -1.40455298 -1.2463529 -1.055206706
#> [925,] -0.58354723 -1.23923939 -1.2463529 -0.999991503
#> [926,] 0.85513500 0.85473267 0.8161403 0.730084872
#> [927,] -1.07572800 -0.85350770 -0.5588552 1.797578806
#> [928,] -0.46996706 -1.01882128 -1.2463529 -0.797535757
#> [929,] -0.62140729 -0.85350770 -1.2463529 -1.423308063
#> [930,] -1.71934900 1.40577795 1.5036381 0.932540618
#> [931,] -1.68148894 1.40577795 1.5036381 1.576717992
#> [932,] 1.30945571 1.46088248 0.1286426 1.116591296
#> [933,] -0.58354723 -0.90861223 -1.2463529 -1.036801639
#> [934,] -1.68148894 0.68941909 2.1911358 1.116591296
#> [935,] -1.71934900 1.18535984 1.5036381 0.969350754
#> [936,] -0.39424694 -0.79840317 -1.2463529 -1.276067520
#> [937,] 1.08229535 1.57109153 0.8161403 0.858920347
#> [938,] -0.65926735 -0.96371675 -1.2463529 -0.852750960
#> [939,] -0.58354723 -1.01882128 -1.2463529 -1.404902995
#> [940,] 0.85513500 0.63431456 0.1286426 0.251553109
#> [941,] -0.50782711 -1.29434392 -1.2463529 -1.368092859
#> [942,] -0.65926735 -0.85350770 -1.2463529 -0.907966164
#> [943,] -1.71934900 1.24046437 1.5036381 1.944819348
#> [944,] -0.69712741 -1.18413487 -1.2463529 -0.907966164
#> [945,] -1.71934900 0.30368739 2.1911358 1.613528128
#> [946,] -1.75720905 0.96494173 1.5036381 1.447882517
#> [947,] 0.74155483 1.46088248 0.1286426 0.766895008
#> [948,] -0.62140729 -1.29434392 -1.2463529 -1.147232046
#> [949,] -1.68148894 1.35067342 1.5036381 1.171806500
#> [950,] -0.62140729 -1.18413487 -1.2463529 -1.257662452
#> [951,] -1.68148894 0.46900097 2.1911358 1.705553467
#> [952,] 0.89299506 1.46088248 0.1286426 1.245426771
#> [953,] -0.65926735 -1.07392581 -1.2463529 -0.926371232
#> [954,] 0.96871518 -0.08204431 1.5036381 -0.779130689
#> [955,] -1.71934900 1.13025531 1.5036381 1.392667314
#> [956,] -0.35638688 -0.90861223 -1.2463529 -1.036801639
#> [957,] 0.24937406 0.96494173 -0.5588552 -1.331282724
#> [958,] 0.93085512 -1.01882128 -0.5588552 0.950945686
#> [959,] -1.75720905 1.29556889 1.5036381 1.042971025
#> [960,] -0.43210700 -1.18413487 -1.2463529 -1.386497927
#> [961,] -0.43210700 -1.45965751 -1.2463529 -0.871156028
#> [962,] -1.71934900 0.30368739 0.8161403 1.337452110
#> [963,] -1.71934900 1.07515078 1.5036381 1.503097721
#> [964,] -0.43210700 -1.01882128 -1.2463529 -0.889561096
#> [965,] 1.04443530 1.57109153 0.8161403 0.674869669
#> [966,] -0.54568717 -1.29434392 -1.2463529 -1.423308063
#> [967,] -0.58354723 -0.79840317 -1.2463529 -0.797535757
#> [968,] 1.23373559 1.07515078 0.1286426 0.564439262
#> [969,] 1.08229535 0.85473267 0.1286426 0.785300076
#> [970,] 1.23373559 1.57109153 0.8161403 0.288363244
#> [971,] 1.08229535 0.79962814 0.8161403 1.190211568
#> [972,] -0.46996706 -1.29434392 -1.2463529 -0.926371232
#> [973,] 1.23373559 0.90983720 0.8161403 0.527629126
#> [974,] -1.71934900 0.52410550 2.1911358 0.748489940
#> [975,] 0.24937406 0.30368739 0.8161403 0.435603787
#> [976,] -0.73498747 -0.96371675 -1.2463529 -0.834345893
#> [977,] -0.65926735 -1.01882128 -1.2463529 -1.239257385
#> [978,] -0.46996706 -1.12903034 -1.2463529 -0.889561096
#> [979,] -0.58354723 -1.40455298 -1.2463529 -1.349687792
#> [980,] -0.69712741 -1.12903034 -1.2463529 -0.926371232
#> [981,] -0.46996706 -1.07392581 -1.2463529 -0.797535757
#> [982,] -1.71934900 0.85473267 1.5036381 1.595123060
#> [983,] -0.65926735 -0.90861223 -1.2463529 -1.018396571
#> [984,] 1.15801547 1.13025531 0.8161403 0.895730483
#> [985,] -1.71934900 0.46900097 2.1911358 1.429477449
#> [986,] 1.19587553 1.24046437 0.1286426 1.300641975
#> [987,] 0.77941488 1.57109153 0.8161403 0.288363244
#> [988,] -1.71934900 -0.90861223 -1.2463529 0.803705143
#> [989,] -0.69712741 -0.79840317 -1.2463529 -1.294472588
#> [990,] 1.27159565 1.29556889 -1.2463529 -0.411029333
#> [991,] -1.68148894 0.68941909 1.5036381 0.877325415
#> [992,] -0.43210700 -1.23923939 -1.2463529 -1.349687792
#> [993,] -0.50782711 -0.85350770 -1.2463529 -1.276067520
#> [994,] -1.71934900 0.96494173 1.5036381 1.024565957
#> [995,] 1.34731577 1.40577795 0.1286426 1.300641975
#> [996,] -0.65926735 -1.01882128 -1.2463529 -0.871156028
#> [997,] -0.62140729 -1.34944845 -1.2463529 -1.331282724
#> [998,] -1.68148894 0.68941909 2.1911358 1.116591296
#> [999,] 1.38517582 0.74452361 0.8161403 1.024565957
#> [1000,] -1.68148894 0.35879192 1.5036381 0.730084872
#> [1001,] -1.75720905 1.02004625 1.5036381 0.969350754
#> [1002,] -0.43210700 -1.18413487 -1.2463529 -1.018396571
#> [1003,] -0.54568717 -1.07392581 -1.2463529 -1.239257385
#> [1004,] 0.70369477 0.68941909 0.8161403 0.840515279
#> [1005,] 1.30945571 1.46088248 0.8161403 1.245426771
#> [1006,] -1.68148894 0.90983720 1.5036381 1.595123060
#> [1007,] -1.75720905 0.35879192 1.5036381 0.932540618
#> [1008,] -0.35638688 -1.23923939 -1.2463529 -1.202447249
#> [1009,] -0.43210700 -1.45965751 -1.2463529 -0.871156028
#> [1010,] 0.96871518 -0.08204431 1.5036381 -0.779130689
#> [1011,] -0.58354723 -1.12903034 -1.2463529 -0.797535757
#> [1012,] -0.69712741 -0.79840317 -1.2463529 -1.368092859
#> [1013,] -0.50782711 -1.34944845 -1.2463529 -0.815940825
#> [1014,] 1.00657524 1.57109153 0.1286426 0.472413923
#> [1015,] 0.62797465 0.74452361 0.8161403 0.748489940
#> [1016,] 0.13579388 1.57109153 -1.2463529 -0.797535757
#> [1017,] -0.39424694 -1.01882128 -1.2463529 -1.368092859
#> [1018,] 0.55225453 0.68941909 1.5036381 -0.779130689
#> [1019,] -1.71934900 0.85473267 1.5036381 0.858920347
#> [1020,] 0.70369477 0.68941909 0.8161403 0.840515279
#> [1021,] -0.43210700 -1.01882128 -1.2463529 -0.999991503
#> [1022,] -1.71934900 1.18535984 1.5036381 0.914135550
#> [1023,] -0.46996706 -1.23923939 -1.2463529 -1.257662452
#> [1024,] -0.35638688 -1.29434392 -1.2463529 -1.147232046
#> [1025,] -0.46996706 -1.01882128 -1.2463529 -0.981586435
#> [1026,] -1.71934900 1.18535984 1.5036381 0.730084872
#> [1027,] -0.35638688 -0.90861223 -1.2463529 -1.368092859
#> [1028,] -1.68148894 1.29556889 1.5036381 0.766895008
#> [1029,] -1.71934900 0.63431456 1.5036381 1.650338263
#> [1030,] -0.39424694 -0.96371675 -1.2463529 -1.165637113
#> [1031,] -1.71934900 0.41389645 1.5036381 1.300641975
#> [1032,] 1.04443530 0.63431456 0.8161403 1.042971025
#> [1033,] 0.70369477 1.35067342 0.1286426 0.509224058
#> [1034,] 1.00657524 0.85473267 0.1286426 0.656464601
#> [1035,] -0.54568717 -1.34944845 -1.2463529 -1.257662452
#> [1036,] -1.71934900 0.96494173 1.5036381 1.411072381
#> [1037,] -0.39424694 -1.23923939 -1.2463529 -0.963181367
#> [1038,] -1.71934900 1.35067342 2.1911358 1.558312924
#> [1039,] 1.15801547 0.90983720 0.8161403 1.190211568
#> [1040,] -0.58354723 -1.45965751 -1.2463529 -1.128826978
#> [1041,] 1.15801547 1.57109153 0.8161403 0.472413923
#> [1042,] -1.68148894 1.07515078 2.1911358 1.539907856
#> [1043,] -0.69712741 -1.23923939 -1.2463529 -0.963181367
#> [1044,] -0.43210700 -1.18413487 -1.2463529 -1.349687792
#> [1045,] -0.39424694 -1.23923939 -1.2463529 -1.276067520
#> [1046,] -0.92428776 0.68941909 2.1911358 -1.294472588
#> [1047,] -0.50782711 -0.85350770 -1.2463529 -1.036801639
#> [1048,] -0.65926735 -1.07392581 -1.2463529 -1.073611774
#> [1049,] 1.23373559 0.96494173 0.1286426 0.932540618
#> [1050,] 1.30945571 1.57109153 0.8161403 0.325173380
#> [1051,] 1.15801547 1.57109153 0.8161403 0.987755822
#> [1052,] -1.71934900 1.02004625 1.5036381 1.797578806
#> [1053,] -1.75720905 1.29556889 2.1911358 0.969350754
#> [1054,] -0.39424694 -1.34944845 -1.2463529 -0.963181367
#> [1055,] 1.00657524 0.57921003 0.8161403 0.306768312
#> [1056,] -0.46996706 -1.01882128 -1.2463529 -1.331282724
#> [1057,] 1.27159565 0.79962814 0.8161403 1.319047042
#> [1058,] -1.75720905 0.90983720 2.1911358 1.134996364
#> [1059,] 1.30945571 1.35067342 0.8161403 0.730084872
#> [1060,] -0.43210700 -1.29434392 -1.2463529 -1.018396571
#> [1061,] -1.71934900 1.40577795 2.1911358 1.484692653
#> [1062,] 1.08229535 1.18535984 0.1286426 0.877325415
#> [1063,] -0.65926735 -0.85350770 -1.2463529 -0.871156028
#> [1064,] 1.08229535 1.24046437 0.8161403 0.343578448
#> [1065,] -0.65926735 1.57109153 0.8161403 -1.220852317
#> [1066,] 1.04443530 0.90983720 0.8161403 0.656464601
#> [1067,] -1.68148894 0.63431456 1.5036381 0.748489940
#> [1068,] -0.43210700 -1.01882128 -1.2463529 -0.999991503
#> [1069,] -1.68148894 0.63431456 1.5036381 1.447882517
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#> [1073,] -1.68148894 0.68941909 1.5036381 1.539907856
#> [1074,] 1.38517582 0.85473267 0.1286426 0.417198719
#> [1075,] -0.69712741 -0.90861223 -1.2463529 -1.404902995
#> [1076,] 0.85513500 -0.30246242 -0.5588552 -0.723915486
#> [1077,] 1.30945571 0.57921003 0.8161403 1.024565957
#> [1078,] -0.54568717 -1.12903034 -1.2463529 -1.404902995
#> [1079,] -1.68148894 0.63431456 1.5036381 0.748489940
#> [1080,] 0.70369477 1.51598701 0.1286426 0.546034194
#> [1081,] 0.89299506 1.13025531 0.8161403 0.932540618
#> [1082,] -1.68148894 1.35067342 1.5036381 1.411072381
#> [1083,] -0.54568717 -1.40455298 -1.2463529 -0.871156028
#> [1084,] -1.71934900 0.41389645 1.5036381 1.319047042
#> [1085,] -0.16708659 0.63431456 0.8161403 0.840515279
#> [1086,] 0.96871518 1.57109153 0.8161403 0.582844330
#> [1087,] -0.69712741 -1.07392581 -1.2463529 -1.147232046
#> [1088,] -0.46996706 -1.18413487 -1.2463529 -1.220852317
#> [1089,] 1.00657524 1.07515078 0.8161403 1.337452110
#> [1090,] -0.35638688 -1.23923939 -1.2463529 -1.018396571
#> [1091,] 0.85513500 1.57109153 0.1286426 0.914135550
#> [1092,] -1.75720905 0.68941909 1.5036381 1.006160889
#> [1093,] -1.68148894 1.40577795 1.5036381 1.355857178
#> [1094,] 0.93085512 1.57109153 0.8161403 1.042971025
#> [1095,] -0.58354723 -1.34944845 -1.2463529 -1.055206706
#> [1096,] -0.58354723 -1.18413487 -1.2463529 -1.368092859
#> [1097,] -0.73498747 -0.79840317 -1.2463529 -1.128826978
#> [1098,] -1.68148894 1.02004625 1.5036381 0.932540618
#> [1099,] 0.74155483 0.52410550 0.8161403 0.435603787
#> [1100,] -1.68148894 1.35067342 2.1911358 1.355857178
#> [1101,] 0.28723412 1.18535984 0.8161403 -0.742320553
#> [1102,] 0.47653441 -0.52288053 0.8161403 -0.098143180
#> [1103,] -1.75720905 0.46900097 1.5036381 1.852794009
#> [1104,] -0.65926735 -1.23923939 -1.2463529 -1.092016842
#> [1105,] -0.43210700 -0.85350770 -1.2463529 -0.834345893
#> [1106,] -1.71934900 0.57921003 2.1911358 1.134996364
#> [1107,] -1.75720905 1.18535984 1.5036381 1.392667314
#> [1108,] -0.54568717 -1.29434392 -1.2463529 -1.184042181
#> [1109,] -0.43210700 -1.18413487 -1.2463529 -1.257662452
#> [1110,] -0.58354723 -1.01882128 -1.2463529 -0.963181367
#> [1111,] -1.71934900 0.68941909 2.1911358 0.858920347
#> [1112,] -0.65926735 -0.90861223 -1.2463529 -1.073611774
#> [1113,] -0.54568717 -1.18413487 -1.2463529 -0.999991503
#> [1114,] -0.73498747 -1.29434392 -1.2463529 -1.220852317
#> [1115,] -1.71934900 0.85473267 1.5036381 1.889604145
#> [1116,] 1.00657524 1.40577795 0.8161403 1.098186229
#> [1117,] -1.68148894 1.07515078 1.5036381 1.926414280
#> [1118,] -1.68148894 1.18535984 1.5036381 1.447882517
#> [1119,] -0.62140729 -1.23923939 -1.2463529 -1.055206706
#> [1120,] -0.50782711 -1.34944845 -1.2463529 -1.257662452
#> [1121,] 0.74155483 0.90983720 0.1286426 0.656464601
#> [1122,] -0.58354723 -0.35756695 -1.2463529 1.705553467
#> [1123,] -0.54568717 -1.34944845 -1.2463529 -1.257662452
#> [1124,] -0.65926735 -1.12903034 -1.2463529 -0.815940825
#> [1125,] -1.68148894 0.85473267 1.5036381 1.871199077
#> [1126,] -0.54568717 -0.90861223 -1.2463529 -0.907966164
#> [1127,] -1.68148894 0.85473267 2.1911358 1.374262246
#> [1128,] -0.62140729 -0.90861223 -1.2463529 -0.871156028
#> [1129,] -0.69712741 -0.79840317 -1.2463529 -0.852750960
#> [1130,] -0.50782711 -1.01882128 -1.2463529 -1.128826978
#> [1131,] -0.39424694 -0.96371675 -1.2463529 -1.368092859
#> [1132,] -0.35638688 -1.45965751 -1.2463529 -1.202447249
#> [1133,] 0.96871518 0.74452361 0.1286426 0.877325415
#> [1134,] -1.68148894 0.90983720 2.1911358 1.871199077
#> [1135,] 1.27159565 -0.35756695 0.8161403 -0.153358383
#> [1136,] -1.75720905 0.63431456 1.5036381 0.858920347
#> [1137,] -1.68148894 1.18535984 1.5036381 0.914135550
#> [1138,] 0.66583471 1.57109153 0.8161403 0.914135550
#> [1139,] -0.69712741 -0.96371675 -1.2463529 -1.312877656
#> [1140,] 0.70369477 0.96494173 0.8161403 1.024565957
#> [1141,] 1.12015541 1.51598701 0.8161403 0.822110211
#> [1142,] 0.66583471 1.51598701 0.8161403 1.079781161
#> [1143,] -0.62140729 -1.29434392 -1.2463529 -0.797535757
#> [1144,] -1.68148894 0.96494173 1.5036381 1.116591296
#> [1145,] -0.65926735 -1.07392581 -1.2463529 -1.073611774
#> [1146,] -1.34074841 -1.18413487 0.8161403 -1.257662452
#> [1147,] 1.23373559 0.90983720 0.8161403 0.527629126
#> [1148,] 1.19587553 1.02004625 0.1286426 0.969350754
#> [1149,] -0.46996706 -0.90861223 -1.2463529 -1.239257385
#> [1150,] 1.08229535 1.24046437 0.8161403 1.079781161
#> [1151,] 0.81727494 1.02004625 0.1286426 0.619654465
#> [1152,] -0.54568717 -1.07392581 -1.2463529 -1.404902995
#> [1153,] -1.71934900 0.74452361 1.5036381 1.153401432
#> [1154,] -0.46996706 -0.79840317 -1.2463529 -0.797535757
#> [1155,] -1.60576882 0.35879192 1.5036381 -0.944776300
#> [1156,] 0.70369477 0.96494173 0.8161403 0.472413923
#> [1157,] -1.75720905 0.63431456 1.5036381 0.950945686
#> [1158,] -0.65926735 -0.85350770 -1.2463529 -0.779130689
#> [1159,] -0.39424694 -0.96371675 -1.2463529 -1.257662452
#> [1160,] -0.35638688 -1.23923939 -1.2463529 -1.018396571
#> [1161,] 0.77941488 1.13025531 0.1286426 0.656464601
#> [1162,] -1.68148894 1.46088248 1.5036381 0.858920347
#> [1163,] -1.71934900 0.68941909 0.8161403 1.834388941
#> [1164,] -0.62140729 -1.18413487 -1.2463529 -1.239257385
#> [1165,] -0.54568717 -1.29434392 -1.2463529 -1.184042181
#> [1166,] -1.07572800 -0.96371675 2.1911358 1.374262246
#> [1167,] -0.69712741 -1.01882128 -1.2463529 -1.036801639
#> [1168,] -1.71934900 1.24046437 1.5036381 0.950945686
#> [1169,] -0.62140729 -0.19225336 -1.2463529 1.447882517
#> [1170,] -1.75720905 1.18535984 2.1911358 1.227021703
#> [1171,] -0.69712741 -0.79840317 -1.2463529 -1.036801639
#> [1172,] -0.69712741 -0.79840317 -1.2463529 -1.368092859
#> [1173,] 1.27159565 1.51598701 0.8161403 0.987755822
#> [1174,] -0.54568717 -1.29434392 -1.2463529 -1.073611774
#> [1175,] 1.30945571 1.40577795 0.1286426 1.006160889
#> [1176,] 1.30945571 0.68941909 0.8161403 0.325173380
#> [1177,] 1.04443530 1.29556889 0.1286426 0.877325415
#> [1178,] -0.46996706 -0.79840317 -1.2463529 -0.815940825
#> [1179,] -0.46996706 -1.23923939 -1.2463529 -1.331282724
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#> [1181,] -0.58354723 -0.85350770 -1.2463529 -1.331282724
#> [1182,] 1.00657524 0.68941909 0.8161403 0.748489940
#> [1183,] 0.77941488 1.51598701 0.1286426 0.914135550
#> [1184,] 1.27159565 1.29556889 0.1286426 1.319047042
#> [1185,] 1.30945571 1.35067342 0.1286426 1.006160889
#> [1186,] -0.62140729 -1.18413487 0.1286426 1.668743331
#> [1187,] -0.73498747 -1.29434392 -1.2463529 -1.239257385
#> [1188,] -0.28066676 1.18535984 -0.5588552 0.288363244
#> [1189,] -0.73498747 -1.12903034 -1.2463529 -1.368092859
#> [1190,] -0.69712741 -0.85350770 -1.2463529 -0.871156028
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#> [1192,] -1.71934900 1.18535984 1.5036381 1.576717992
#> [1193,] -1.75720905 1.46088248 1.5036381 1.245426771
#> [1194,] -0.65926735 -1.01882128 -1.2463529 -0.852750960
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#> [1197,] -1.75720905 1.35067342 1.5036381 1.024565957
#> [1198,] -1.68148894 1.29556889 1.5036381 1.521502788
#> [1199,] -0.58354723 -1.07392581 -1.2463529 -0.889561096
#> [1200,] -0.65926735 -1.45965751 -1.2463529 -0.871156028
#> [1201,] 0.81727494 1.51598701 0.8161403 0.454008855
#> [1202,] -0.58354723 -0.96371675 -1.2463529 -1.184042181
#> [1203,] 1.00657524 1.24046437 0.8161403 0.601249397
#> [1204,] -0.88642770 -0.63308959 -1.2463529 1.411072381
#> [1205,] 1.27159565 1.13025531 0.8161403 0.619654465
#> [1206,] -0.65926735 -1.18413487 -1.2463529 -1.312877656
#> [1207,] -0.65926735 -0.96371675 -1.2463529 -1.257662452
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#> [1209,] -0.69712741 -1.29434392 -1.2463529 -0.797535757
#> [1210,] 0.89299506 -0.68819411 0.1286426 -1.184042181
#> [1211,] 1.19587553 0.90983720 0.8161403 0.674869669
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#> [1213,] 0.85513500 -0.02693978 -0.5588552 0.840515279
#> [1214,] 1.38517582 0.57921003 0.8161403 1.134996364
#> [1215,] -0.58354723 -0.85350770 -1.2463529 -1.220852317
#> [1216,] 1.00657524 0.74452361 0.1286426 0.361983516
#> [1217,] -1.68148894 1.24046437 1.5036381 1.337452110
#> [1218,] -0.62140729 -1.29434392 -1.2463529 -0.797535757
#> [1219,] 1.12015541 1.07515078 0.8161403 0.417198719
#> [1220,] -0.46996706 -1.01882128 -1.2463529 -0.852750960
#> [1221,] -1.75720905 0.85473267 2.1911358 1.687148399
#> [1222,] -0.39424694 -0.90861223 -1.2463529 -1.165637113
#> [1223,] -1.71934900 1.24046437 1.5036381 1.539907856
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#> [1227,] -1.68148894 0.85473267 2.1911358 1.447882517
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#> [1229,] -1.56790876 0.19347833 0.1286426 1.355857178
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#> [1231,] -0.01564635 -0.63308959 -0.5588552 -0.429434401
#> [1232,] -0.69712741 -1.23923939 -1.2463529 -0.926371232
#> [1233,] 0.96871518 1.57109153 0.1286426 0.914135550
#> [1234,] -0.69712741 -0.90861223 -1.2463529 -1.165637113
#> [1235,] -0.39424694 -1.01882128 -1.2463529 -1.368092859
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#> [1239,] -0.62140729 -1.18413487 -1.2463529 -1.257662452
#> [1240,] 0.89299506 1.13025531 0.8161403 0.932540618
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#> [1242,] -0.54568717 -0.90861223 -1.2463529 -1.018396571
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#> [1246,] 1.19587553 1.07515078 0.1286426 0.454008855
#> [1247,] -1.68148894 0.13837381 1.5036381 1.595123060
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#> [1253,] -1.75720905 0.85473267 0.8161403 1.098186229
#> [1254,] 1.34731577 1.24046437 0.8161403 0.987755822
#> [1255,] 0.21151400 0.79962814 0.1286426 -0.134953315
#> [1256,] -0.58354723 -1.01882128 -1.2463529 -0.963181367
#> [1257,] 1.23373559 1.51598701 0.8161403 1.079781161
#> [1258,] -1.71934900 0.96494173 2.1911358 1.503097721
#> [1259,] -0.62140729 -0.85350770 -1.2463529 -0.797535757
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#> [1262,] -1.71934900 0.41389645 1.5036381 1.797578806
#> [1263,] 0.85513500 1.46088248 0.8161403 0.656464601
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#> [1265,] -0.43210700 -1.34944845 -1.2463529 -0.871156028
#> [1266,] -1.75720905 0.74452361 1.5036381 1.042971025
#> [1267,] -0.39424694 -1.40455298 -1.2463529 -0.926371232
#> [1268,] -1.71934900 0.52410550 1.5036381 1.797578806
#> [1269,] -1.71934900 0.85473267 1.5036381 1.595123060
#> [1270,] 1.08229535 1.40577795 0.8161403 0.877325415
#> [1271,] -1.75720905 0.63431456 1.5036381 1.521502788
#> [1272,] -1.71934900 0.30368739 1.5036381 1.134996364
#> [1273,] -1.75720905 0.85473267 2.1911358 1.687148399
#> [1274,] 0.40081430 1.57109153 0.8161403 1.208616635
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#> [1280,] -1.75720905 1.13025531 1.5036381 1.061376093
#> [1281,] -1.71934900 0.85473267 2.1911358 1.576717992
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#> [1285,] -1.75720905 1.29556889 2.1911358 0.969350754
#> [1286,] -1.71934900 0.63431456 1.5036381 1.116591296
#> [1287,] -1.75720905 0.79962814 1.5036381 1.392667314
#> [1288,] -0.62140729 -1.18413487 -1.2463529 -0.963181367
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#> [1291,] -0.50782711 -0.85350770 -1.2463529 -0.999991503
#> [1292,] -1.75720905 0.35879192 1.5036381 1.098186229
#> [1293,] 0.43867436 -0.96371675 -0.5588552 -0.687105350
#> [1294,] 0.89299506 1.13025531 0.8161403 0.932540618
#> [1295,] -0.58354723 -1.01882128 -1.2463529 -0.963181367
#> [1296,] -1.75720905 0.57921003 1.5036381 0.858920347
#> [1297,] 1.00657524 1.07515078 0.8161403 0.527629126
#> [1298,] 1.08229535 0.90983720 0.1286426 1.098186229
#> [1299,] -1.68148894 1.35067342 1.5036381 1.963224416
#> [1300,] -0.62140729 -1.12903034 -1.2463529 -1.184042181
#> [1301,] 0.77941488 1.57109153 0.8161403 0.288363244
#> [1302,] 1.00657524 1.18535984 0.1286426 0.785300076
#> [1303,] -1.71934900 1.13025531 2.1911358 0.914135550
#> [1304,] -0.62140729 -1.18413487 -1.2463529 -1.239257385
#> [1305,] -0.92428776 -0.85350770 0.1286426 0.638059533
#> [1306,] -1.68148894 1.02004625 1.5036381 1.098186229
#> [1307,] -1.75720905 1.18535984 1.5036381 1.705553467
#> [1308,] 1.30945571 1.51598701 0.1286426 1.024565957
#> [1309,] -1.68148894 0.68941909 1.5036381 0.877325415
#> [1310,] -0.39424694 -1.40455298 -1.2463529 -0.889561096
#> [1311,] -1.71934900 0.63431456 1.5036381 1.687148399
#> [1312,] 1.19587553 1.57109153 0.8161403 1.061376093
#> [1313,] -1.68148894 0.46900097 1.5036381 1.503097721
#> [1314,] -0.50782711 -0.96371675 -1.2463529 -0.871156028
#> [1315,] 0.81727494 1.51598701 0.8161403 0.454008855
#> [1316,] -1.75720905 1.35067342 1.5036381 0.766895008
#> [1317,] -1.68148894 0.52410550 0.8161403 1.539907856
#> [1318,] -1.75720905 0.46900097 1.5036381 1.797578806
#> [1319,] -0.69712741 -1.07392581 -1.2463529 -1.110421910
#> [1320,] -1.68148894 -0.90861223 -1.2463529 -1.220852317
#> [1321,] 0.93085512 0.63431456 -1.2463529 0.141122702
#> [1322,] -1.68148894 0.41389645 1.5036381 1.631933195
#> [1323,] -1.68148894 1.18535984 0.8161403 -1.165637113
#> [1324,] 0.74155483 0.79962814 0.8161403 0.619654465
#> [1325,] -0.46996706 -0.96371675 -1.2463529 -0.926371232
#> [1326,] -1.75720905 1.35067342 1.5036381 0.766895008
#> [1327,] -1.68148894 0.46900097 1.5036381 1.852794009
#> [1328,] -1.56790876 -0.90861223 1.5036381 -0.521459740
#> [1329,] -1.71934900 0.63431456 2.1911358 1.337452110
#> [1330,] -0.46996706 -1.12903034 -1.2463529 -0.999991503
#> [1331,] 1.04443530 1.13025531 0.8161403 1.171806500
#> [1332,] 0.89299506 1.02004625 0.8161403 1.098186229
#> [1333,] -1.75720905 1.02004625 2.1911358 1.576717992
#> [1334,] 1.19587553 0.68941909 0.1286426 1.116591296
#> [1335,] -1.71934900 0.74452361 2.1911358 1.392667314
#> [1336,] -1.68148894 0.46900097 1.5036381 1.447882517
#> [1337,] -1.71934900 0.57921003 1.5036381 1.153401432
#> [1338,] -0.50782711 -0.79840317 -1.2463529 -1.036801639
#> [1339,] 1.00657524 1.46088248 0.8161403 0.564439262
#> [1340,] -1.71934900 0.74452361 2.1911358 1.061376093
#> [1341,] -0.88642770 -1.18413487 -1.2463529 -1.257662452
#> [1342,] -0.35638688 -1.18413487 -1.2463529 -0.852750960
#> [1343,] 1.38517582 1.18535984 0.8161403 0.674869669
#> [1344,] -0.65926735 -1.01882128 -1.2463529 -0.852750960
#> [1345,] -1.68148894 0.57921003 1.5036381 1.227021703
#> [1346,] 1.08229535 1.35067342 0.1286426 0.803705143
#> [1347,] -0.35638688 -1.01882128 -1.2463529 -1.386497927
#> [1348,] -0.69712741 -1.29434392 -1.2463529 -1.220852317
#> [1349,] -0.46996706 -1.12903034 -1.2463529 -1.386497927
#> [1350,] 0.85513500 0.85473267 0.8161403 0.969350754
#> [1351,] -0.62140729 -0.90861223 -1.2463529 -0.944776300
#> [1352,] -0.54568717 -1.23923939 -1.2463529 -1.055206706
#> [1353,] -0.54568717 -0.85350770 -1.2463529 -0.907966164
#> [1354,] -0.69712741 -1.01882128 -1.2463529 -1.331282724
#> [1355,] 0.89299506 0.96494173 0.8161403 0.656464601
#> [1356,] -0.58354723 -1.40455298 -1.2463529 -1.349687792
#> [1357,] -1.71934900 0.41389645 1.5036381 1.613528128
#> [1358,] 0.93085512 0.63431456 -1.2463529 0.141122702
#> [1359,] -1.68148894 0.68941909 1.5036381 0.877325415
#> [1360,] -0.54568717 -1.29434392 -1.2463529 -1.239257385
#> [1361,] -0.58354723 -1.12903034 -1.2463529 -1.073611774
#> [1362,] -0.39424694 -1.23923939 -1.2463529 -0.999991503
#> [1363,] -0.39424694 -1.34944845 -1.2463529 -0.797535757
#> [1364,] -0.43210700 -1.45965751 -1.2463529 -0.871156028
#> [1365,] 0.85513500 1.57109153 0.8161403 0.601249397
#> [1366,] -0.54568717 -1.34944845 -1.2463529 -1.202447249
#> [1367,] -0.58354723 -1.40455298 -1.2463529 -1.110421910
#> [1368,] -0.92428776 1.29556889 1.5036381 0.582844330
#> [1369,] -0.54568717 -1.07392581 -1.2463529 -0.815940825
#> [1370,] -0.92428776 0.30368739 0.1286426 -0.999991503
#> [1371,] -1.71934900 1.13025531 1.5036381 1.006160889
#> [1372,] 1.30945571 -0.08204431 0.8161403 0.049097363
#> [1373,] -1.68148894 0.46900097 1.5036381 1.503097721
#> [1374,] 1.38517582 1.51598701 0.8161403 0.950945686
#> [1375,] -0.50782711 -1.18413487 -1.2463529 -0.889561096
#> [1376,] -0.50782711 -0.79840317 -1.2463529 -0.907966164
#> [1377,] -1.71934900 1.46088248 1.5036381 1.190211568
#> [1378,] -0.65926735 -0.90861223 -1.2463529 -1.036801639
#> [1379,] -0.50782711 -1.34944845 -1.2463529 -1.184042181
#> [1380,] -1.15144811 -1.40455298 0.1286426 0.196337905
#> [1381,] -0.54568717 -1.40455298 -1.2463529 -0.963181367
#> [1382,] 0.85513500 1.18535984 0.1286426 0.398793651
#> [1383,] -0.69712741 -1.40455298 -1.2463529 -1.165637113
#> [1384,] -0.46996706 -1.18413487 -1.2463529 -1.257662452
#> [1385,] -1.71934900 0.63431456 1.5036381 1.006160889
#> [1386,] -1.68148894 0.57921003 1.5036381 1.227021703
#> [1387,] -0.46996706 -1.34944845 -1.2463529 -1.220852317
#> [1388,] -1.75720905 0.41389645 1.5036381 1.319047042
#> [1389,] 0.96871518 1.13025531 0.8161403 0.656464601
#> [1390,] -1.75720905 1.07515078 1.5036381 1.319047042
#> [1391,] -1.75720905 0.74452361 1.5036381 1.723958534
#> [1392,] -1.71934900 1.02004625 0.8161403 1.098186229
#> [1393,] -0.39424694 -1.29434392 -1.2463529 -1.092016842
#> [1394,] -0.43210700 -0.96371675 -1.2463529 -0.999991503
#> [1395,] -0.43210700 -1.12903034 -1.2463529 -1.165637113
#> [1396,] -1.75720905 0.63431456 1.5036381 0.950945686
#> [1397,] -1.68148894 0.52410550 1.5036381 1.871199077
#> [1398,] -0.39424694 -1.12903034 -1.2463529 -0.797535757
#> [1399,] 0.89299506 0.85473267 0.8161403 1.061376093
#> [1400,] -1.75720905 1.02004625 2.1911358 1.705553467
#> [1401,] -0.43210700 -1.01882128 -1.2463529 -0.815940825
#> [1402,] -1.68148894 0.46900097 1.5036381 0.969350754
#> [1403,] -0.54568717 -1.34944845 -1.2463529 -1.202447249
#> [1404,] 1.15801547 1.29556889 0.8161403 1.208616635
#> [1405,] -1.71934900 0.68941909 0.8161403 1.742363602
#> [1406,] -0.43210700 -1.07392581 -1.2463529 -1.386497927
#> [1407,] -0.65926735 -1.45965751 -1.2463529 -0.871156028
#> [1408,] 0.96871518 1.18535984 0.8161403 1.227021703
#> [1409,] -0.73498747 -1.29434392 -1.2463529 -0.871156028
#> [1410,] -0.50782711 -1.01882128 -0.5588552 -0.079738112
#> [1411,] -0.58354723 -0.85350770 -1.2463529 -1.018396571
#> [1412,] -1.68148894 0.30368739 1.5036381 1.613528128
#> [1413,] -0.69712741 -1.18413487 -1.2463529 -1.147232046
#> [1414,] -1.68148894 1.18535984 1.5036381 1.337452110
#> [1415,] 1.19587553 0.63431456 0.8161403 1.171806500
#> [1416,] -0.69712741 -1.12903034 -1.2463529 -1.404902995
#> [1417,] -1.75720905 1.02004625 1.5036381 1.687148399
#> [1418,] 1.27159565 0.90983720 0.8161403 0.454008855
#> [1419,] -0.39424694 -1.12903034 -1.2463529 -0.797535757
#> [1420,] 1.04443530 1.29556889 0.8161403 0.325173380
#> [1421,] -0.58354723 -1.34944845 -1.2463529 -1.092016842
#> [1422,] 1.30945571 1.57109153 0.8161403 0.325173380
#> [1423,] 1.38517582 0.96494173 0.1286426 0.693274736
#> [1424,] 0.89299506 0.68941909 0.1286426 0.674869669
#> [1425,] -0.39424694 -0.96371675 -1.2463529 -1.368092859
#> [1426,] 1.12015541 0.74452361 0.8161403 1.171806500
#> [1427,] -1.68148894 0.63431456 2.1911358 0.950945686
#> [1428,] 1.15801547 1.18535984 0.8161403 0.361983516
#> [1429,] -1.68148894 0.96494173 1.5036381 1.797578806
#> time_spend_company
#> [1,] -0.4656229
#> [2,] -1.2373385
#> [3,] -0.4656229
#> [4,] -1.2373385
#> [5,] 0.3060927
#> [6,] 0.3060927
#> [7,] 0.3060927
#> [8,] -1.2373385
#> [9,] -1.2373385
#> [10,] 0.3060927
#> [11,] -0.4656229
#> [12,] -0.4656229
#> [13,] 1.8495239
#> [14,] 1.0778083
#> [15,] -0.4656229
#> [16,] -0.4656229
#> [17,] -0.4656229
#> [18,] -0.4656229
#> [19,] -0.4656229
#> [20,] 0.3060927
#> [21,] 0.3060927
#> [22,] -1.2373385
#> [23,] -0.4656229
#> [24,] -0.4656229
#> [25,] 0.3060927
#> [26,] -1.2373385
#> [27,] -1.2373385
#> [28,] -1.2373385
#> [29,] -1.2373385
#> [30,] 1.0778083
#> [31,] -0.4656229
#> [32,] -1.2373385
#> [33,] -1.2373385
#> [34,] -0.4656229
#> [35,] -0.4656229
#> [36,] -1.2373385
#> [37,] -0.4656229
#> [38,] -1.2373385
#> [39,] -1.2373385
#> [40,] 0.3060927
#> [41,] 1.8495239
#> [42,] 1.8495239
#> [43,] 4.9363862
#> [44,] -0.4656229
#> [45,] 0.3060927
#> [46,] -1.2373385
#> [47,] -1.2373385
#> [48,] 0.3060927
#> [49,] -1.2373385
#> [50,] -1.2373385
#> [51,] -1.2373385
#> [52,] -0.4656229
#> [53,] -0.4656229
#> [54,] -0.4656229
#> [55,] -0.4656229
#> [56,] -0.4656229
#> [57,] -0.4656229
#> [58,] -0.4656229
#> [59,] -1.2373385
#> [60,] -1.2373385
#> [61,] -1.2373385
#> [62,] -1.2373385
#> [63,] -1.2373385
#> [64,] -0.4656229
#> [65,] -1.2373385
#> [66,] -1.2373385
#> [67,] -0.4656229
#> [68,] -1.2373385
#> [69,] 1.8495239
#> [70,] -1.2373385
#> [71,] -0.4656229
#> [72,] -0.4656229
#> [73,] -0.4656229
#> [74,] -1.2373385
#> [75,] 1.8495239
#> [76,] -0.4656229
#> [77,] 2.6212395
#> [78,] 1.0778083
#> [79,] -0.4656229
#> [80,] -0.4656229
#> [81,] -0.4656229
#> [82,] 0.3060927
#> [83,] -0.4656229
#> [84,] -0.4656229
#> [85,] -0.4656229
#> [86,] -0.4656229
#> [87,] 1.8495239
#> [88,] -0.4656229
#> [89,] -0.4656229
#> [90,] 1.0778083
#> [91,] -0.4656229
#> [92,] 0.3060927
#> [93,] -0.4656229
#> [94,] 1.8495239
#> [95,] -0.4656229
#> [96,] -0.4656229
#> [97,] -0.4656229
#> [98,] -0.4656229
#> [99,] -0.4656229
#> [100,] -0.4656229
#> [101,] -1.2373385
#> [102,] -0.4656229
#> [103,] -1.2373385
#> [104,] -0.4656229
#> [105,] -0.4656229
#> [106,] 1.0778083
#> [107,] 0.3060927
#> [108,] 0.3060927
#> [109,] 1.8495239
#> [110,] -0.4656229
#> [111,] 0.3060927
#> [112,] 0.3060927
#> [113,] 0.3060927
#> [114,] -1.2373385
#> [115,] -0.4656229
#> [116,] -0.4656229
#> [117,] -0.4656229
#> [118,] -0.4656229
#> [119,] -1.2373385
#> [120,] 1.8495239
#> [121,] 1.8495239
#> [122,] 0.3060927
#> [123,] -0.4656229
#> [124,] -1.2373385
#> [125,] -1.2373385
#> [126,] -1.2373385
#> [127,] -1.2373385
#> [128,] -0.4656229
#> [129,] -1.2373385
#> [130,] 0.3060927
#> [131,] 0.3060927
#> [132,] -1.2373385
#> [133,] 0.3060927
#> [134,] -0.4656229
#> [135,] -0.4656229
#> [136,] -0.4656229
#> [137,] 0.3060927
#> [138,] -0.4656229
#> [139,] 0.3060927
#> [140,] 0.3060927
#> [141,] -0.4656229
#> [142,] -0.4656229
#> [143,] 1.8495239
#> [144,] -0.4656229
#> [145,] -0.4656229
#> [146,] -0.4656229
#> [147,] -1.2373385
#> [148,] 0.3060927
#> [149,] -0.4656229
#> [150,] 0.3060927
#> [151,] -0.4656229
#> [152,] -0.4656229
#> [153,] -0.4656229
#> [154,] 0.3060927
#> [155,] -0.4656229
#> [156,] -1.2373385
#> [157,] -0.4656229
#> [158,] 0.3060927
#> [159,] -1.2373385
#> [160,] 1.8495239
#> [161,] -0.4656229
#> [162,] -0.4656229
#> [163,] 1.0778083
#> [164,] 0.3060927
#> [165,] 0.3060927
#> [166,] 1.8495239
#> [167,] -0.4656229
#> [168,] 0.3060927
#> [169,] -0.4656229
#> [170,] -0.4656229
#> [171,] -1.2373385
#> [172,] -0.4656229
#> [173,] -0.4656229
#> [174,] -0.4656229
#> [175,] -0.4656229
#> [176,] -0.4656229
#> [177,] 1.8495239
#> [178,] -0.4656229
#> [179,] -1.2373385
#> [180,] 2.6212395
#> [181,] -1.2373385
#> [182,] 0.3060927
#> [183,] -1.2373385
#> [184,] -0.4656229
#> [185,] -0.4656229
#> [186,] -1.2373385
#> [187,] -0.4656229
#> [188,] 0.3060927
#> [189,] -1.2373385
#> [190,] 2.6212395
#> [191,] -0.4656229
#> [192,] -1.2373385
#> [193,] -0.4656229
#> [194,] -0.4656229
#> [195,] -0.4656229
#> [196,] 0.3060927
#> [197,] 0.3060927
#> [198,] -0.4656229
#> [199,] -0.4656229
#> [200,] -0.4656229
#> [201,] 0.3060927
#> [202,] -0.4656229
#> [203,] 4.9363862
#> [204,] 1.8495239
#> [205,] -0.4656229
#> [206,] -0.4656229
#> [207,] -1.2373385
#> [208,] 1.8495239
#> [209,] 0.3060927
#> [210,] -1.2373385
#> [211,] -0.4656229
#> [212,] -0.4656229
#> [213,] -0.4656229
#> [214,] -0.4656229
#> [215,] -1.2373385
#> [216,] -0.4656229
#> [217,] -1.2373385
#> [218,] -1.2373385
#> [219,] -1.2373385
#> [220,] -0.4656229
#> [221,] 0.3060927
#> [222,] -1.2373385
#> [223,] -0.4656229
#> [224,] -0.4656229
#> [225,] 1.0778083
#> [226,] -0.4656229
#> [227,] -1.2373385
#> [228,] -0.4656229
#> [229,] -0.4656229
#> [230,] -0.4656229
#> [231,] -0.4656229
#> [232,] -1.2373385
#> [233,] -0.4656229
#> [234,] -1.2373385
#> [235,] 0.3060927
#> [236,] -0.4656229
#> [237,] 0.3060927
#> [238,] -0.4656229
#> [239,] -1.2373385
#> [240,] -0.4656229
#> [241,] -0.4656229
#> [242,] -0.4656229
#> [243,] -0.4656229
#> [244,] -0.4656229
#> [245,] -1.2373385
#> [246,] 0.3060927
#> [247,] -1.2373385
#> [248,] -0.4656229
#> [249,] -0.4656229
#> [250,] 4.9363862
#> [251,] -1.2373385
#> [252,] 0.3060927
#> [253,] 0.3060927
#> [254,] 4.9363862
#> [255,] -1.2373385
#> [256,] 0.3060927
#> [257,] -0.4656229
#> [258,] -1.2373385
#> [259,] 0.3060927
#> [260,] -1.2373385
#> [261,] -1.2373385
#> [262,] -1.2373385
#> [263,] -1.2373385
#> [264,] -1.2373385
#> [265,] -1.2373385
#> [266,] -0.4656229
#> [267,] 1.8495239
#> [268,] -0.4656229
#> [269,] -1.2373385
#> [270,] 4.9363862
#> [271,] 0.3060927
#> [272,] -0.4656229
#> [273,] -1.2373385
#> [274,] 0.3060927
#> [275,] -0.4656229
#> [276,] -1.2373385
#> [277,] -0.4656229
#> [278,] 0.3060927
#> [279,] -1.2373385
#> [280,] 0.3060927
#> [281,] -0.4656229
#> [282,] -1.2373385
#> [283,] -0.4656229
#> [284,] 0.3060927
#> [285,] -0.4656229
#> [286,] -1.2373385
#> [287,] -1.2373385
#> [288,] -0.4656229
#> [289,] -0.4656229
#> [290,] -1.2373385
#> [291,] -1.2373385
#> [292,] -1.2373385
#> [293,] 0.3060927
#> [294,] -0.4656229
#> [295,] 0.3060927
#> [296,] -0.4656229
#> [297,] -1.2373385
#> [298,] 1.8495239
#> [299,] -1.2373385
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#> [301,] -0.4656229
#> [302,] -1.2373385
#> [303,] -1.2373385
#> [304,] 1.0778083
#> [305,] 0.3060927
#> [306,] -0.4656229
#> [307,] -0.4656229
#> [308,] 2.6212395
#> [309,] -0.4656229
#> [310,] -0.4656229
#> [311,] -0.4656229
#> [312,] 1.8495239
#> [313,] -0.4656229
#> [314,] -0.4656229
#> [315,] 0.3060927
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#> [317,] 4.9363862
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#> [320,] -0.4656229
#> [321,] -1.2373385
#> [322,] -0.4656229
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#> [326,] -1.2373385
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#> [328,] -0.4656229
#> [329,] -0.4656229
#> [330,] -0.4656229
#> [331,] -1.2373385
#> [332,] -0.4656229
#> [333,] -0.4656229
#> [334,] -1.2373385
#> [335,] -1.2373385
#> [336,] -1.2373385
#> [337,] 4.9363862
#> [338,] -0.4656229
#> [339,] -1.2373385
#> [340,] 2.6212395
#> [341,] -0.4656229
#> [342,] 0.3060927
#> [343,] 2.6212395
#> [344,] -1.2373385
#> [345,] -0.4656229
#> [346,] 0.3060927
#> [347,] -0.4656229
#> [348,] -0.4656229
#> [349,] 0.3060927
#> [350,] -1.2373385
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#> [352,] -0.4656229
#> [353,] -0.4656229
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#> [356,] -1.2373385
#> [357,] -0.4656229
#> [358,] -0.4656229
#> [359,] -0.4656229
#> [360,] -1.2373385
#> [361,] 4.9363862
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#> [365,] -0.4656229
#> [366,] -1.2373385
#> [367,] -0.4656229
#> [368,] 0.3060927
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#> [370,] -0.4656229
#> [371,] -1.2373385
#> [372,] -0.4656229
#> [373,] 0.3060927
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#> [376,] -0.4656229
#> [377,] -0.4656229
#> [378,] -1.2373385
#> [379,] -1.2373385
#> [380,] -0.4656229
#> [381,] 0.3060927
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#> [383,] -1.2373385
#> [384,] -0.4656229
#> [385,] -1.2373385
#> [386,] -1.2373385
#> [387,] 0.3060927
#> [388,] -0.4656229
#> [389,] -1.2373385
#> [390,] -1.2373385
#> [391,] -0.4656229
#> [392,] 0.3060927
#> [393,] 3.3929551
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#> [395,] -1.2373385
#> [396,] -1.2373385
#> [397,] -0.4656229
#> [398,] -0.4656229
#> [399,] 1.0778083
#> [400,] -0.4656229
#> [401,] -0.4656229
#> [402,] -0.4656229
#> [403,] 1.0778083
#> [404,] 4.9363862
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#> [406,] -1.2373385
#> [407,] -1.2373385
#> [408,] -0.4656229
#> [409,] 2.6212395
#> [410,] -0.4656229
#> [411,] -0.4656229
#> [412,] 0.3060927
#> [413,] -0.4656229
#> [414,] -1.2373385
#> [415,] -1.2373385
#> [416,] -1.2373385
#> [417,] 1.0778083
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#> [420,] -1.2373385
#> [421,] -0.4656229
#> [422,] 0.3060927
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#> [424,] 2.6212395
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#> [427,] 4.9363862
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#> [429,] 0.3060927
#> [430,] 0.3060927
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#> [433,] -0.4656229
#> [434,] -0.4656229
#> [435,] -0.4656229
#> [436,] -0.4656229
#> [437,] -0.4656229
#> [438,] 0.3060927
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#> [441,] -1.2373385
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#> [443,] -0.4656229
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#> [450,] -1.2373385
#> [451,] -1.2373385
#> [452,] -1.2373385
#> [453,] -1.2373385
#> [454,] -0.4656229
#> [455,] -1.2373385
#> [456,] 4.9363862
#> [457,] 1.0778083
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#> [459,] -1.2373385
#> [460,] 0.3060927
#> [461,] -0.4656229
#> [462,] 2.6212395
#> [463,] 3.3929551
#> [464,] -1.2373385
#> [465,] 3.3929551
#> [466,] 2.6212395
#> [467,] 2.6212395
#> [468,] 0.3060927
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#> [470,] 0.3060927
#> [471,] -1.2373385
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#> [473,] -0.4656229
#> [474,] -1.2373385
#> [475,] -1.2373385
#> [476,] -1.2373385
#> [477,] -0.4656229
#> [478,] 4.9363862
#> [479,] -0.4656229
#> [480,] -0.4656229
#> [481,] -1.2373385
#> [482,] 2.6212395
#> [483,] 0.3060927
#> [484,] -1.2373385
#> [485,] -0.4656229
#> [486,] -0.4656229
#> [487,] 4.9363862
#> [488,] 4.9363862
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#> [491,] 1.0778083
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#> [494,] -0.4656229
#> [495,] -0.4656229
#> [496,] -0.4656229
#> [497,] 2.6212395
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#> [500,] 0.3060927
#> [501,] -0.4656229
#> [502,] -0.4656229
#> [503,] 1.8495239
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#> [505,] 0.3060927
#> [506,] -0.4656229
#> [507,] 2.6212395
#> [508,] -0.4656229
#> [509,] -0.4656229
#> [510,] 4.9363862
#> [511,] -0.4656229
#> [512,] 4.9363862
#> [513,] -1.2373385
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#> [515,] 1.0778083
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#> [553,] 3.3929551
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#> [566,] -0.4656229
#> [567,] -0.4656229
#> [568,] -0.4656229
#> [569,] -1.2373385
#> [570,] 1.0778083
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#> [573,] -0.4656229
#> [574,] 1.0778083
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#> [890,] 1.0778083
#> [891,] 0.3060927
#> [892,] -0.4656229
#> [893,] -0.4656229
#> [894,] 0.3060927
#> [895,] -0.4656229
#> [896,] -0.4656229
#> [897,] -0.4656229
#> [898,] 0.3060927
#> [899,] -0.4656229
#> [900,] 1.0778083
#> [901,] 0.3060927
#> [902,] 0.3060927
#> [903,] 1.0778083
#> [904,] -0.4656229
#> [905,] -0.4656229
#> [906,] -0.4656229
#> [907,] 0.3060927
#> [908,] -0.4656229
#> [909,] 1.0778083
#> [910,] -0.4656229
#> [911,] 1.0778083
#> [912,] 0.3060927
#> [913,] -0.4656229
#> [914,] -0.4656229
#> [915,] -0.4656229
#> [916,] -0.4656229
#> [917,] 1.0778083
#> [918,] -0.4656229
#> [919,] 1.0778083
#> [920,] 0.3060927
#> [921,] 1.0778083
#> [922,] 1.0778083
#> [923,] -0.4656229
#> [924,] -0.4656229
#> [925,] -0.4656229
#> [926,] 1.0778083
#> [927,] -0.4656229
#> [928,] -0.4656229
#> [929,] -0.4656229
#> [930,] 1.0778083
#> [931,] 1.0778083
#> [932,] 1.8495239
#> [933,] -0.4656229
#> [934,] 0.3060927
#> [935,] 0.3060927
#> [936,] -0.4656229
#> [937,] 1.0778083
#> [938,] -0.4656229
#> [939,] -0.4656229
#> [940,] 1.8495239
#> [941,] -0.4656229
#> [942,] -0.4656229
#> [943,] 0.3060927
#> [944,] -0.4656229
#> [945,] 0.3060927
#> [946,] 0.3060927
#> [947,] 1.0778083
#> [948,] -0.4656229
#> [949,] 0.3060927
#> [950,] -0.4656229
#> [951,] 0.3060927
#> [952,] 1.0778083
#> [953,] -0.4656229
#> [954,] 0.3060927
#> [955,] 0.3060927
#> [956,] -0.4656229
#> [957,] 0.3060927
#> [958,] 1.0778083
#> [959,] 0.3060927
#> [960,] -0.4656229
#> [961,] -0.4656229
#> [962,] 0.3060927
#> [963,] 0.3060927
#> [964,] -0.4656229
#> [965,] 1.0778083
#> [966,] -0.4656229
#> [967,] -0.4656229
#> [968,] 1.8495239
#> [969,] 1.8495239
#> [970,] 1.8495239
#> [971,] 1.0778083
#> [972,] -0.4656229
#> [973,] 1.0778083
#> [974,] 1.0778083
#> [975,] 0.3060927
#> [976,] -0.4656229
#> [977,] -0.4656229
#> [978,] -0.4656229
#> [979,] -0.4656229
#> [980,] -0.4656229
#> [981,] -0.4656229
#> [982,] 0.3060927
#> [983,] -0.4656229
#> [984,] 1.0778083
#> [985,] 0.3060927
#> [986,] 1.0778083
#> [987,] 1.0778083
#> [988,] 0.3060927
#> [989,] -0.4656229
#> [990,] 1.0778083
#> [991,] 0.3060927
#> [992,] -0.4656229
#> [993,] -0.4656229
#> [994,] 1.0778083
#> [995,] 1.8495239
#> [996,] -0.4656229
#> [997,] -0.4656229
#> [998,] 0.3060927
#> [999,] 1.0778083
#> [1000,] 0.3060927
#> [1001,] 0.3060927
#> [1002,] -0.4656229
#> [1003,] -0.4656229
#> [1004,] 1.0778083
#> [1005,] 1.0778083
#> [1006,] 0.3060927
#> [1007,] 0.3060927
#> [1008,] -0.4656229
#> [1009,] -0.4656229
#> [1010,] 0.3060927
#> [1011,] -0.4656229
#> [1012,] -0.4656229
#> [1013,] -0.4656229
#> [1014,] 1.8495239
#> [1015,] 1.8495239
#> [1016,] 1.0778083
#> [1017,] -0.4656229
#> [1018,] 0.3060927
#> [1019,] 0.3060927
#> [1020,] 1.0778083
#> [1021,] -0.4656229
#> [1022,] 0.3060927
#> [1023,] -0.4656229
#> [1024,] -0.4656229
#> [1025,] -0.4656229
#> [1026,] 0.3060927
#> [1027,] -0.4656229
#> [1028,] 0.3060927
#> [1029,] 0.3060927
#> [1030,] -0.4656229
#> [1031,] 0.3060927
#> [1032,] 1.0778083
#> [1033,] 1.0778083
#> [1034,] 1.0778083
#> [1035,] -0.4656229
#> [1036,] 0.3060927
#> [1037,] -0.4656229
#> [1038,] 0.3060927
#> [1039,] 1.0778083
#> [1040,] -0.4656229
#> [1041,] 1.0778083
#> [1042,] 0.3060927
#> [1043,] -0.4656229
#> [1044,] -0.4656229
#> [1045,] -0.4656229
#> [1046,] 1.0778083
#> [1047,] -0.4656229
#> [1048,] -0.4656229
#> [1049,] 1.0778083
#> [1050,] 1.0778083
#> [1051,] 1.0778083
#> [1052,] 1.0778083
#> [1053,] 0.3060927
#> [1054,] -0.4656229
#> [1055,] 1.8495239
#> [1056,] -0.4656229
#> [1057,] 1.0778083
#> [1058,] 0.3060927
#> [1059,] 1.0778083
#> [1060,] -0.4656229
#> [1061,] 0.3060927
#> [1062,] 1.0778083
#> [1063,] -0.4656229
#> [1064,] 1.8495239
#> [1065,] 0.3060927
#> [1066,] 1.0778083
#> [1067,] 0.3060927
#> [1068,] -0.4656229
#> [1069,] 0.3060927
#> [1070,] -0.4656229
#> [1071,] 1.0778083
#> [1072,] -1.2373385
#> [1073,] 0.3060927
#> [1074,] 1.8495239
#> [1075,] -0.4656229
#> [1076,] -0.4656229
#> [1077,] 1.0778083
#> [1078,] -0.4656229
#> [1079,] 0.3060927
#> [1080,] 1.0778083
#> [1081,] 1.8495239
#> [1082,] 0.3060927
#> [1083,] -0.4656229
#> [1084,] 0.3060927
#> [1085,] 0.3060927
#> [1086,] 1.0778083
#> [1087,] -0.4656229
#> [1088,] -0.4656229
#> [1089,] 1.8495239
#> [1090,] -0.4656229
#> [1091,] 1.0778083
#> [1092,] 0.3060927
#> [1093,] 0.3060927
#> [1094,] 1.0778083
#> [1095,] -0.4656229
#> [1096,] -0.4656229
#> [1097,] -0.4656229
#> [1098,] 0.3060927
#> [1099,] 1.0778083
#> [1100,] 1.0778083
#> [1101,] -0.4656229
#> [1102,] 1.0778083
#> [1103,] 1.0778083
#> [1104,] -0.4656229
#> [1105,] -0.4656229
#> [1106,] 0.3060927
#> [1107,] 0.3060927
#> [1108,] -0.4656229
#> [1109,] -0.4656229
#> [1110,] -0.4656229
#> [1111,] 0.3060927
#> [1112,] -0.4656229
#> [1113,] -0.4656229
#> [1114,] -0.4656229
#> [1115,] 0.3060927
#> [1116,] 1.0778083
#> [1117,] 0.3060927
#> [1118,] 0.3060927
#> [1119,] -0.4656229
#> [1120,] -0.4656229
#> [1121,] 1.0778083
#> [1122,] 1.0778083
#> [1123,] -0.4656229
#> [1124,] -0.4656229
#> [1125,] 0.3060927
#> [1126,] -0.4656229
#> [1127,] 0.3060927
#> [1128,] -0.4656229
#> [1129,] -0.4656229
#> [1130,] -0.4656229
#> [1131,] -0.4656229
#> [1132,] -0.4656229
#> [1133,] 1.8495239
#> [1134,] 0.3060927
#> [1135,] 1.8495239
#> [1136,] 0.3060927
#> [1137,] 0.3060927
#> [1138,] 1.8495239
#> [1139,] -0.4656229
#> [1140,] 1.0778083
#> [1141,] 1.0778083
#> [1142,] 1.0778083
#> [1143,] -0.4656229
#> [1144,] 0.3060927
#> [1145,] -0.4656229
#> [1146,] 1.8495239
#> [1147,] 1.0778083
#> [1148,] 1.0778083
#> [1149,] -0.4656229
#> [1150,] 1.0778083
#> [1151,] 1.0778083
#> [1152,] -0.4656229
#> [1153,] 0.3060927
#> [1154,] -0.4656229
#> [1155,] -1.2373385
#> [1156,] 1.8495239
#> [1157,] 0.3060927
#> [1158,] -0.4656229
#> [1159,] -0.4656229
#> [1160,] -0.4656229
#> [1161,] 1.0778083
#> [1162,] 0.3060927
#> [1163,] 1.0778083
#> [1164,] -0.4656229
#> [1165,] -0.4656229
#> [1166,] -0.4656229
#> [1167,] -0.4656229
#> [1168,] 0.3060927
#> [1169,] 1.0778083
#> [1170,] 0.3060927
#> [1171,] -0.4656229
#> [1172,] -0.4656229
#> [1173,] 1.0778083
#> [1174,] -0.4656229
#> [1175,] 1.0778083
#> [1176,] 1.0778083
#> [1177,] 1.0778083
#> [1178,] -0.4656229
#> [1179,] -0.4656229
#> [1180,] -0.4656229
#> [1181,] -0.4656229
#> [1182,] 1.0778083
#> [1183,] 1.0778083
#> [1184,] 1.0778083
#> [1185,] 1.0778083
#> [1186,] -0.4656229
#> [1187,] -0.4656229
#> [1188,] 1.8495239
#> [1189,] -0.4656229
#> [1190,] -0.4656229
#> [1191,] -0.4656229
#> [1192,] 0.3060927
#> [1193,] 0.3060927
#> [1194,] -0.4656229
#> [1195,] -0.4656229
#> [1196,] -0.4656229
#> [1197,] 0.3060927
#> [1198,] 0.3060927
#> [1199,] -0.4656229
#> [1200,] -0.4656229
#> [1201,] 1.0778083
#> [1202,] -0.4656229
#> [1203,] 1.0778083
#> [1204,] 0.3060927
#> [1205,] 1.0778083
#> [1206,] -0.4656229
#> [1207,] -0.4656229
#> [1208,] -0.4656229
#> [1209,] -0.4656229
#> [1210,] -0.4656229
#> [1211,] 1.0778083
#> [1212,] -0.4656229
#> [1213,] 1.0778083
#> [1214,] 1.0778083
#> [1215,] -0.4656229
#> [1216,] 1.0778083
#> [1217,] 0.3060927
#> [1218,] -0.4656229
#> [1219,] 1.0778083
#> [1220,] -0.4656229
#> [1221,] 0.3060927
#> [1222,] -0.4656229
#> [1223,] 0.3060927
#> [1224,] -0.4656229
#> [1225,] -0.4656229
#> [1226,] -0.4656229
#> [1227,] 1.0778083
#> [1228,] -0.4656229
#> [1229,] 1.0778083
#> [1230,] -0.4656229
#> [1231,] 0.3060927
#> [1232,] -0.4656229
#> [1233,] 1.0778083
#> [1234,] -0.4656229
#> [1235,] -0.4656229
#> [1236,] 0.3060927
#> [1237,] -0.4656229
#> [1238,] -1.2373385
#> [1239,] -0.4656229
#> [1240,] 1.8495239
#> [1241,] -0.4656229
#> [1242,] -0.4656229
#> [1243,] 0.3060927
#> [1244,] -0.4656229
#> [1245,] 1.0778083
#> [1246,] 1.0778083
#> [1247,] 1.0778083
#> [1248,] -0.4656229
#> [1249,] -0.4656229
#> [1250,] 0.3060927
#> [1251,] -0.4656229
#> [1252,] -0.4656229
#> [1253,] 0.3060927
#> [1254,] 1.0778083
#> [1255,] 0.3060927
#> [1256,] -0.4656229
#> [1257,] 1.8495239
#> [1258,] 0.3060927
#> [1259,] -0.4656229
#> [1260,] -0.4656229
#> [1261,] -0.4656229
#> [1262,] 1.0778083
#> [1263,] 1.8495239
#> [1264,] 0.3060927
#> [1265,] -0.4656229
#> [1266,] 0.3060927
#> [1267,] -0.4656229
#> [1268,] 0.3060927
#> [1269,] 0.3060927
#> [1270,] 1.0778083
#> [1271,] 0.3060927
#> [1272,] 0.3060927
#> [1273,] 0.3060927
#> [1274,] 1.0778083
#> [1275,] -0.4656229
#> [1276,] -0.4656229
#> [1277,] 0.3060927
#> [1278,] -0.4656229
#> [1279,] -0.4656229
#> [1280,] 0.3060927
#> [1281,] 0.3060927
#> [1282,] -0.4656229
#> [1283,] -0.4656229
#> [1284,] -0.4656229
#> [1285,] 0.3060927
#> [1286,] 0.3060927
#> [1287,] 0.3060927
#> [1288,] -0.4656229
#> [1289,] -0.4656229
#> [1290,] -0.4656229
#> [1291,] -0.4656229
#> [1292,] 0.3060927
#> [1293,] 1.0778083
#> [1294,] 1.8495239
#> [1295,] -0.4656229
#> [1296,] 0.3060927
#> [1297,] 1.0778083
#> [1298,] 1.0778083
#> [1299,] 0.3060927
#> [1300,] -0.4656229
#> [1301,] 1.0778083
#> [1302,] 1.0778083
#> [1303,] 0.3060927
#> [1304,] -0.4656229
#> [1305,] -1.2373385
#> [1306,] 0.3060927
#> [1307,] 0.3060927
#> [1308,] 1.8495239
#> [1309,] 0.3060927
#> [1310,] -0.4656229
#> [1311,] 0.3060927
#> [1312,] 1.0778083
#> [1313,] 0.3060927
#> [1314,] -0.4656229
#> [1315,] 1.0778083
#> [1316,] 0.3060927
#> [1317,] 0.3060927
#> [1318,] 1.0778083
#> [1319,] -0.4656229
#> [1320,] -0.4656229
#> [1321,] -0.4656229
#> [1322,] 0.3060927
#> [1323,] 1.0778083
#> [1324,] 1.0778083
#> [1325,] -0.4656229
#> [1326,] 0.3060927
#> [1327,] 0.3060927
#> [1328,] 1.0778083
#> [1329,] 0.3060927
#> [1330,] -0.4656229
#> [1331,] 1.8495239
#> [1332,] 1.0778083
#> [1333,] 1.0778083
#> [1334,] 1.8495239
#> [1335,] 0.3060927
#> [1336,] 0.3060927
#> [1337,] 0.3060927
#> [1338,] -0.4656229
#> [1339,] 1.0778083
#> [1340,] 0.3060927
#> [1341,] 1.0778083
#> [1342,] -0.4656229
#> [1343,] 1.0778083
#> [1344,] -0.4656229
#> [1345,] 0.3060927
#> [1346,] 1.0778083
#> [1347,] -0.4656229
#> [1348,] -0.4656229
#> [1349,] -0.4656229
#> [1350,] 1.0778083
#> [1351,] -0.4656229
#> [1352,] -0.4656229
#> [1353,] -0.4656229
#> [1354,] -0.4656229
#> [1355,] 1.0778083
#> [1356,] -0.4656229
#> [1357,] 0.3060927
#> [1358,] -0.4656229
#> [1359,] 0.3060927
#> [1360,] -0.4656229
#> [1361,] -0.4656229
#> [1362,] -0.4656229
#> [1363,] -0.4656229
#> [1364,] -0.4656229
#> [1365,] 1.0778083
#> [1366,] -0.4656229
#> [1367,] -0.4656229
#> [1368,] 1.0778083
#> [1369,] -0.4656229
#> [1370,] -0.4656229
#> [1371,] 0.3060927
#> [1372,] 0.3060927
#> [1373,] 0.3060927
#> [1374,] 1.8495239
#> [1375,] -0.4656229
#> [1376,] -0.4656229
#> [1377,] 0.3060927
#> [1378,] -0.4656229
#> [1379,] -0.4656229
#> [1380,] 0.3060927
#> [1381,] -0.4656229
#> [1382,] 1.0778083
#> [1383,] -0.4656229
#> [1384,] -0.4656229
#> [1385,] 0.3060927
#> [1386,] 0.3060927
#> [1387,] -0.4656229
#> [1388,] 0.3060927
#> [1389,] 1.0778083
#> [1390,] 0.3060927
#> [1391,] 0.3060927
#> [1392,] 0.3060927
#> [1393,] -0.4656229
#> [1394,] -0.4656229
#> [1395,] -0.4656229
#> [1396,] 0.3060927
#> [1397,] 0.3060927
#> [1398,] -0.4656229
#> [1399,] 1.0778083
#> [1400,] 0.3060927
#> [1401,] -0.4656229
#> [1402,] 0.3060927
#> [1403,] -0.4656229
#> [1404,] 1.8495239
#> [1405,] 0.3060927
#> [1406,] -0.4656229
#> [1407,] -0.4656229
#> [1408,] 1.0778083
#> [1409,] -0.4656229
#> [1410,] 0.3060927
#> [1411,] -0.4656229
#> [1412,] 0.3060927
#> [1413,] -0.4656229
#> [1414,] 0.3060927
#> [1415,] 1.0778083
#> [1416,] -0.4656229
#> [1417,] 0.3060927
#> [1418,] 1.0778083
#> [1419,] -0.4656229
#> [1420,] 1.0778083
#> [1421,] -0.4656229
#> [1422,] 1.0778083
#> [1423,] 1.0778083
#> [1424,] 1.0778083
#> [1425,] -0.4656229
#> [1426,] 1.0778083
#> [1427,] 1.0778083
#> [1428,] 1.0778083
#> [1429,] 0.3060927
#> attr(,"scaled:center")
#> satisfaction_level last_evaluation number_project
#> 0.5541327 0.7148888 3.8128829
#> average_monthly_hours time_spend_company
#> 203.3323998 3.6033608
#> attr(,"scaled:scale")
#> satisfaction_level last_evaluation number_project
#> 0.2641306 0.1814733 1.4545502
#> average_monthly_hours time_spend_company
#> 54.3328615 1.2958142After we have finished normalizing the data, we need to find the optimal value of K to use in the kNN model. In practice, choosing the value of k depends on the complexity of the data being analyzed and the number of observations/rows in the training data.
#> [1] 75.58439K-optimum: 75.58439
D. Prediction
Using the k value that we have obtained, try to predict test_y using train_x and train_y data. To create the kNN model, please use the knn() function and save the prediction results in the model_knn object. Use the following code to help you:
library(class)
model_knn <- knn(train = train_knn_xs,
test = test_knn_xs,
cl =train_knn_y,
k =76)
head(model_knn)#> [1] 0 0 0 0 0 0
#> Levels: 0 1#> [1] 10E. Evaluation
#> [1] "0" "1"#> [1] "0" "1"library(caret)
knn_cm <- confusionMatrix(data = test_knn$pred_label,
reference = as.factor(test_knn$left),
positive = "1")
knn_cm#> Confusion Matrix and Statistics
#>
#> Reference
#> Prediction 0 1
#> 0 646 57
#> 1 63 663
#>
#> Accuracy : 0.916
#> 95% CI : (0.9004, 0.9299)
#> No Information Rate : 0.5038
#> P-Value [Acc > NIR] : <0.0000000000000002
#>
#> Kappa : 0.832
#>
#> Mcnemar's Test P-Value : 0.6481
#>
#> Sensitivity : 0.9208
#> Specificity : 0.9111
#> Pos Pred Value : 0.9132
#> Neg Pred Value : 0.9189
#> Prevalence : 0.5038
#> Detection Rate : 0.4640
#> Detection Prevalence : 0.5080
#> Balanced Accuracy : 0.9160
#>
#> 'Positive' Class : 1
#> Model Evaluation Logistic Regression and K-NN
logistic_sum <- data_frame(Accuracy = log_cm$overall[1],
Recall = log_cm$byClass[1],
Specificity = log_cm$byClass[2],
Precision = log_cm$byClass[3])
knn_summ <- data_frame(Accuracy = knn_cm$overall[1],
Recall = knn_cm$byClass[1],
Specificity = knn_cm$byClass[2],
Precision = knn_cm$byClass[3])4. CONCLUSION
Based on the evaluation of both models, the k-Nearest Neighbors (kNN) algorithm outperforms the Logistic Regression model. The kNN model achieved an accuracy of 91.6% with a sensitivity of 91.11% and a specificity of 92.08%, indicating superior performance in correctly identifying both positive and negative cases. It also has a higher Kappa value of 0.7815, demonstrating strong agreement beyond chance. In contrast, the Logistic Regression model achieved a lower accuracy of 76.63%, with sensitivity of 76.25% and specificity of 77.01%. While it is still effective, it does not match the kNN model’s performance, particularly in detecting positives and balancing the overall accuracy. Therefore, the kNN model is the better choice for this dataset, providing more reliable predictions.
The kNN model outperforms the logistic regression model in terms of accuracy, sensitivity, and precision. It is better at predicting employee turnover, especially in identifying employees who are likely to leave. The logistic regression model provides valuable insights into the effect of each predictor on turnover but may not be as effective in classification as the kNN model.
Recommendation: Given the higher accuracy and sensitivity of the kNN model, it may be preferable for predicting employee turnover.