Multiple linear regression and binary logistic regression models
Abdellah AitElmouden | Gabriel Abreu | Jered Ataky | Patrick Maloney
4/13/2021
Overview
This assignment is about to explore, to analyze and to model a data set containing approximately 8000 records representing a customer at an auto insurance company. Each record has two response variables. The first response variable, TARGET_FLAG, is a 1 or a 0. A “1” means that the person was in a car crash. A zero means that the person was not in a car crash. The second response variable is TARGET_AMT. This value is zero if the person did not crash their car. But if they did crash their car, this number will be a value greater than zero. Your objective is to build multiple linear regression and binary logistic regression models on the df1ing data to predict the probability that a person will crash their car and also the amount of money it will cost if the person does crash their car. You can only use the variables given to you (or variables that you derive from the variables provided).
Data exploration
Below is a short description of the variables of interest in the data set:
We need to make some cleaning of data such as removing the index, and special characters on certain variables. Below is the head of the data…
Summary table
Visualization
Outliers
The following diagram shows the outliers for all the variables(numerical), both dependent and independent.
Correlation
Below is the correlation between the numerical variables…
## TARGET_FLAG TARGET_AMT KIDSDRIV AGE HOMEKIDS
## TARGET_FLAG 1.00000000 0.53992929 0.097295404 -0.103649398 0.115481537
## TARGET_AMT 0.53992929 1.00000000 0.056857228 -0.046745810 0.068857861
## KIDSDRIV 0.09729540 0.05685723 1.000000000 -0.072361631 0.463046635
## AGE -0.10364940 -0.04674581 -0.072361631 1.000000000 -0.442383841
## HOMEKIDS 0.11548154 0.06885786 0.463046635 -0.442383841 1.000000000
## YOJ -0.06658661 -0.02144631 0.048112090 0.139566052 0.090416449
## TRAVTIME 0.05149130 0.03270817 0.008979590 0.004555303 -0.007787772
## TIF -0.07718644 -0.04525925 -0.003423442 0.002871951 0.004673246
## CLM_FREQ 0.22338169 0.11515694 0.035087170 -0.026312189 0.030695809
## MVR_PTS 0.22526236 0.13770829 0.055019621 -0.073523273 0.062776101
## CAR_AGE -0.10435770 -0.06283345 -0.055877063 0.182184524 -0.156534495
## YOJ TRAVTIME TIF CLM_FREQ MVR_PTS
## TARGET_FLAG -0.06658661 0.051491295 -0.077186438 0.223381685 0.225262361
## TARGET_AMT -0.02144631 0.032708168 -0.045259254 0.115156936 0.137708292
## KIDSDRIV 0.04811209 0.008979590 -0.003423442 0.035087170 0.055019621
## AGE 0.13956605 0.004555303 0.002871951 -0.026312189 -0.073523273
## HOMEKIDS 0.09041645 -0.007787772 0.004673246 0.030695809 0.062776101
## YOJ 1.00000000 -0.015762889 0.029302946 -0.030658029 -0.039172617
## TRAVTIME -0.01576289 1.000000000 -0.009343232 0.009306981 0.009937566
## TIF 0.02930295 -0.009343232 1.000000000 -0.024972898 -0.037174513
## CLM_FREQ -0.03065803 0.009306981 -0.024972898 1.000000000 0.400121265
## MVR_PTS -0.03917262 0.009937566 -0.037174513 0.400121265 1.000000000
## CAR_AGE 0.06122969 -0.037055196 0.009125709 -0.011538390 -0.019363647
## CAR_AGE
## TARGET_FLAG -0.104357704
## TARGET_AMT -0.062833451
## KIDSDRIV -0.055877063
## AGE 0.182184524
## HOMEKIDS -0.156534495
## YOJ 0.061229694
## TRAVTIME -0.037055196
## TIF 0.009125709
## CLM_FREQ -0.011538390
## MVR_PTS -0.019363647
## CAR_AGE 1.000000000Here’s the correlation matrix visualization…
There is a little bit of correlation between HomeKids and Kidsdriv, and MVR_PTS and CLM_FREQ
Data Preparation
Missing values
Let explore the number of missing values in each variable
## CAR_AGE HOME_VAL YOJ INCOME AGE URBANICITY
## 510 464 454 445 6 0
## CAR_TYPE JOB EDUCATION SEX MSTATUS OLDCLAIM
## 0 0 0 0 0 0
## BLUEBOOK MVR_PTS REVOKED CLM_FREQ RED_CAR TIF
## 0 0 0 0 0 0
## CAR_USE TRAVTIME PARENT1 HOMEKIDS KIDSDRIV TARGET_AMT
## 0 0 0 0 0 0
## TARGET_FLAG
## 0## [1] 1879We will use mean and BoxCox transformation for data imputation, but we need to transform little the data for BoxCox transformation… BoxCox needs variable to have value greater or equal to 1
BoxCox iputation prep
Prepare for BoxCox imputation…
## TARGET_FLAG TARGET_AMT KIDSDRIV
## "0" " 0.00000" "0"
## AGE HOMEKIDS YOJ
## "16" "0" " 0"
## PARENT1 TRAVTIME CAR_USE
## "No" " 5" "Commercial"
## TIF RED_CAR CLM_FREQ
## " 1" "no" "0"
## REVOKED MVR_PTS CAR_AGE
## "No" " 0" NA
## INCOME HOME_VAL BLUEBOOK
## " 0" " 0" " 1500"
## OLDCLAIM MSTATUS SEX
## " 0" "No" "F"
## EDUCATION JOB CAR_TYPE
## "<High School" "" "Minivan"
## URBANICITY
## "Highly Rural/ Rural"## $TIF
## Box-Cox Transformation
##
## 7650 data points used to estimate Lambda
##
## Input data summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.00 1.00 4.00 5.36 7.00 25.00
##
## Largest/Smallest: 25
## Sample Skewness: 0.89
##
## Estimated Lambda: 0.2
##
##
## $BLUEBOOK
## Box-Cox Transformation
##
## 7650 data points used to estimate Lambda
##
## Input data summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1500 9315 14440 15720 20820 69740
##
## Largest/Smallest: 46.5
## Sample Skewness: 0.802
##
## Estimated Lambda: 0.5
##
##
## $TRAVTIME
## Box-Cox Transformation
##
## 7650 data points used to estimate Lambda
##
## Input data summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 5.00 23.00 33.00 33.55 44.00 142.00
##
## Largest/Smallest: 28.4
## Sample Skewness: 0.452
##
## Estimated Lambda: 0.7
##
##
## $AGE
## Box-Cox Transformation
##
## 7650 data points used to estimate Lambda
##
## Input data summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 16.00 39.00 45.00 44.81 51.00 81.00
##
## Largest/Smallest: 5.06
## Sample Skewness: -0.0247
##
## Estimated Lambda: 1
## With fudge factor, no transformation is applied
##
##
## $CAR_AGE
## Box-Cox Transformation
##
## 7650 data points used to estimate Lambda
##
## Input data summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.00 2.00 9.00 9.33 13.00 29.00
##
## Largest/Smallest: 29
## Sample Skewness: 0.282
##
## Estimated Lambda: 0.5
##
##
## $YOJ
## Box-Cox Transformation
##
## 7650 data points used to estimate Lambda
##
## Input data summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.00 10.00 12.00 11.55 14.00 24.00
##
## Largest/Smallest: 24
## Sample Skewness: -1.26
##
## Estimated Lambda: 1.6
##
##
## $INCOME
## Box-Cox Transformation
##
## 7650 data points used to estimate Lambda
##
## Input data summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1 29701 54029 61450 83302 367031
##
## Largest/Smallest: 367000
## Sample Skewness: 1.25
##
## Estimated Lambda: 0.4Build Models
Multiple Linear Regression Models
Model 1: Mean full model
Building the first model using all the variables…
##
## Call:
## lm(formula = TARGET_AMT ~ ., data = df_lm)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8934 -3199 -1537 493 99141
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.025e+03 2.095e+03 1.444 0.148807
## KIDSDRIV -1.167e+02 3.378e+02 -0.346 0.729696
## AGE 1.272e+01 2.236e+01 0.569 0.569617
## HOMEKIDS 2.288e+02 2.169e+02 1.055 0.291669
## YOJ 2.451e+01 5.173e+01 0.474 0.635662
## PARENT1Yes 1.406e+02 6.166e+02 0.228 0.819623
## TRAVTIME 3.617e+00 1.169e+01 0.309 0.757114
## CAR_USEPrivate -5.479e+02 5.487e+02 -0.999 0.318094
## TIF -3.882e+01 4.482e+01 -0.866 0.386583
## RED_CARyes -2.473e+02 5.214e+02 -0.474 0.635302
## CLM_FREQ -1.463e+02 1.662e+02 -0.880 0.378836
## REVOKEDYes -1.192e+03 5.427e+02 -2.197 0.028162 *
## MVR_PTS 1.088e+02 7.231e+01 1.504 0.132743
## CAR_AGE -9.230e+01 4.617e+01 -1.999 0.045712 *
## INCOME -9.670e-03 7.073e-03 -1.367 0.171729
## HOME_VAL 1.671e-03 2.112e-03 0.791 0.429070
## BLUEBOOK 1.227e-01 3.196e-02 3.840 0.000127 ***
## OLDCLAIM 3.257e-02 2.364e-02 1.378 0.168373
## MSTATUSYes -8.493e+02 5.218e+02 -1.628 0.103786
## SEXM 1.397e+03 6.880e+02 2.030 0.042451 *
## EDUCATIONBachelors 2.182e+02 6.777e+02 0.322 0.747551
## EDUCATIONHigh School -5.850e+02 5.389e+02 -1.086 0.277780
## EDUCATIONMasters 9.636e+02 1.152e+03 0.836 0.403142
## EDUCATIONPhD 2.460e+03 1.396e+03 1.762 0.078207 .
## JOBBlue Collar 6.499e+02 1.205e+03 0.539 0.589660
## JOBClerical 3.778e+02 1.263e+03 0.299 0.764818
## JOBDoctor -2.073e+03 1.812e+03 -1.144 0.252835
## JOBHome Maker 1.686e+02 1.333e+03 0.126 0.899392
## JOBLawyer 4.172e+02 1.075e+03 0.388 0.697950
## JOBManager -7.283e+02 1.128e+03 -0.646 0.518587
## JOBProfessional 1.389e+03 1.181e+03 1.176 0.239802
## JOBStudent 1.484e+02 1.355e+03 0.110 0.912816
## CAR_TYPEPanel Truck -5.584e+02 1.004e+03 -0.556 0.578258
## CAR_TYPEPickup -2.292e+02 6.279e+02 -0.365 0.715141
## CAR_TYPESports Car 1.074e+03 7.867e+02 1.365 0.172386
## CAR_TYPESUV 9.386e+02 6.968e+02 1.347 0.178104
## CAR_TYPEVan 3.322e+02 8.104e+02 0.410 0.681889
## URBANICITYHighly Urban/ Urban 1.499e+02 7.962e+02 0.188 0.850687
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7817 on 1973 degrees of freedom
## (142 observations deleted due to missingness)
## Multiple R-squared: 0.03181, Adjusted R-squared: 0.01366
## F-statistic: 1.752 on 37 and 1973 DF, p-value: 0.003512Visualization…
Model 2: Stepwise
## Start: AIC=36091.11
## TARGET_AMT ~ KIDSDRIV + AGE + HOMEKIDS + YOJ + PARENT1 + TRAVTIME +
## CAR_USE + TIF + RED_CAR + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS +
## SEX + EDUCATION + JOB + CAR_TYPE + URBANICITY
##
## Df Sum of Sq RSS AIC
## - JOB 8 469943135 1.2103e+11 36083
## - CAR_TYPE 5 253319413 1.2082e+11 36085
## - URBANICITY 1 2165878 1.2057e+11 36089
## - PARENT1 1 3178268 1.2057e+11 36089
## - TRAVTIME 1 5846477 1.2057e+11 36089
## - KIDSDRIV 1 7297697 1.2057e+11 36089
## - YOJ 1 13720342 1.2058e+11 36089
## - RED_CAR 1 13749572 1.2058e+11 36089
## - AGE 1 19763912 1.2058e+11 36089
## - HOME_VAL 1 38228288 1.2060e+11 36090
## - EDUCATION 4 405041171 1.2097e+11 36090
## - TIF 1 45829844 1.2061e+11 36090
## - CLM_FREQ 1 47346961 1.2061e+11 36090
## - CAR_USE 1 60940121 1.2062e+11 36090
## - HOMEKIDS 1 67981141 1.2063e+11 36090
## - INCOME 1 114217654 1.2068e+11 36091
## - OLDCLAIM 1 116027467 1.2068e+11 36091
## <none> 1.2056e+11 36091
## - MVR_PTS 1 138223654 1.2070e+11 36091
## - MSTATUS 1 161861282 1.2073e+11 36092
## - CAR_AGE 1 244258656 1.2081e+11 36093
## - SEX 1 251910571 1.2082e+11 36093
## - REVOKED 1 294856563 1.2086e+11 36094
## - BLUEBOOK 1 901120949 1.2146e+11 36104
##
## Step: AIC=36082.94
## TARGET_AMT ~ KIDSDRIV + AGE + HOMEKIDS + YOJ + PARENT1 + TRAVTIME +
## CAR_USE + TIF + RED_CAR + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS +
## SEX + EDUCATION + CAR_TYPE + URBANICITY
##
## Df Sum of Sq RSS AIC
## - CAR_TYPE 5 236966467 1.2127e+11 36077
## - EDUCATION 4 308229999 1.2134e+11 36080
## - URBANICITY 1 965617 1.2103e+11 36081
## - PARENT1 1 5312998 1.2104e+11 36081
## - TRAVTIME 1 8714537 1.2104e+11 36081
## - KIDSDRIV 1 8789882 1.2104e+11 36081
## - RED_CAR 1 17718790 1.2105e+11 36081
## - AGE 1 22400164 1.2106e+11 36081
## - TIF 1 35799007 1.2107e+11 36082
## - YOJ 1 43615339 1.2108e+11 36082
## - CLM_FREQ 1 46060690 1.2108e+11 36082
## - HOMEKIDS 1 50786527 1.2108e+11 36082
## - HOME_VAL 1 55459128 1.2109e+11 36082
## - OLDCLAIM 1 93964699 1.2113e+11 36082
## - CAR_USE 1 109054463 1.2114e+11 36083
## - INCOME 1 112628408 1.2115e+11 36083
## <none> 1.2103e+11 36083
## - MVR_PTS 1 164427107 1.2120e+11 36084
## - MSTATUS 1 165584306 1.2120e+11 36084
## - CAR_AGE 1 240391833 1.2127e+11 36085
## - SEX 1 248609327 1.2128e+11 36085
## - REVOKED 1 249404349 1.2128e+11 36085
## - BLUEBOOK 1 892963211 1.2193e+11 36096
##
## Step: AIC=36076.87
## TARGET_AMT ~ KIDSDRIV + AGE + HOMEKIDS + YOJ + PARENT1 + TRAVTIME +
## CAR_USE + TIF + RED_CAR + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS +
## SEX + EDUCATION + URBANICITY
##
## Df Sum of Sq RSS AIC
## - EDUCATION 4 293028995 1.2156e+11 36074
## - URBANICITY 1 856675 1.2127e+11 36075
## - PARENT1 1 6956166 1.2128e+11 36075
## - TRAVTIME 1 10004549 1.2128e+11 36075
## - KIDSDRIV 1 15091560 1.2129e+11 36075
## - RED_CAR 1 22955445 1.2129e+11 36075
## - TIF 1 31683557 1.2130e+11 36075
## - YOJ 1 40394006 1.2131e+11 36076
## - CLM_FREQ 1 48329600 1.2132e+11 36076
## - AGE 1 49960692 1.2132e+11 36076
## - HOMEKIDS 1 55516846 1.2133e+11 36076
## - HOME_VAL 1 58416578 1.2133e+11 36076
## - CAR_USE 1 62849650 1.2133e+11 36076
## - OLDCLAIM 1 94247726 1.2136e+11 36076
## - INCOME 1 102728766 1.2137e+11 36077
## <none> 1.2127e+11 36077
## - SEX 1 126458571 1.2140e+11 36077
## - MSTATUS 1 155747969 1.2143e+11 36077
## - MVR_PTS 1 166354304 1.2144e+11 36078
## - REVOKED 1 246739099 1.2152e+11 36079
## - CAR_AGE 1 255944523 1.2153e+11 36079
## - BLUEBOOK 1 1191468027 1.2246e+11 36095
##
## Step: AIC=36073.72
## TARGET_AMT ~ KIDSDRIV + AGE + HOMEKIDS + YOJ + PARENT1 + TRAVTIME +
## CAR_USE + TIF + RED_CAR + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS +
## SEX + URBANICITY
##
## Df Sum of Sq RSS AIC
## - URBANICITY 1 1842097 1.2157e+11 36072
## - PARENT1 1 5746780 1.2157e+11 36072
## - TRAVTIME 1 11362492 1.2158e+11 36072
## - KIDSDRIV 1 12710883 1.2158e+11 36072
## - CAR_USE 1 18809855 1.2158e+11 36072
## - RED_CAR 1 19154959 1.2158e+11 36072
## - YOJ 1 19249674 1.2158e+11 36072
## - INCOME 1 30009939 1.2159e+11 36072
## - TIF 1 33478524 1.2160e+11 36072
## - CLM_FREQ 1 43826138 1.2161e+11 36072
## - HOMEKIDS 1 56286122 1.2162e+11 36073
## - HOME_VAL 1 64738692 1.2163e+11 36073
## - AGE 1 68188686 1.2163e+11 36073
## - OLDCLAIM 1 89443723 1.2165e+11 36073
## - CAR_AGE 1 106343391 1.2167e+11 36073
## <none> 1.2156e+11 36074
## - SEX 1 149903559 1.2171e+11 36074
## - MSTATUS 1 182520593 1.2175e+11 36075
## - MVR_PTS 1 183291459 1.2175e+11 36075
## - REVOKED 1 245461948 1.2181e+11 36076
## - BLUEBOOK 1 1297078713 1.2286e+11 36093
##
## Step: AIC=36071.75
## TARGET_AMT ~ KIDSDRIV + AGE + HOMEKIDS + YOJ + PARENT1 + TRAVTIME +
## CAR_USE + TIF + RED_CAR + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS +
## SEX
##
## Df Sum of Sq RSS AIC
## - PARENT1 1 5693754 1.2157e+11 36070
## - TRAVTIME 1 10766761 1.2158e+11 36070
## - KIDSDRIV 1 12739425 1.2158e+11 36070
## - CAR_USE 1 18874900 1.2158e+11 36070
## - RED_CAR 1 19054285 1.2158e+11 36070
## - YOJ 1 19438380 1.2158e+11 36070
## - INCOME 1 29169043 1.2159e+11 36070
## - TIF 1 33102736 1.2160e+11 36070
## - CLM_FREQ 1 42851795 1.2161e+11 36070
## - HOMEKIDS 1 55811739 1.2162e+11 36071
## - HOME_VAL 1 64662586 1.2163e+11 36071
## - AGE 1 67542493 1.2163e+11 36071
## - OLDCLAIM 1 88398537 1.2165e+11 36071
## - CAR_AGE 1 105826822 1.2167e+11 36072
## <none> 1.2157e+11 36072
## - SEX 1 148981133 1.2171e+11 36072
## - MSTATUS 1 181291557 1.2175e+11 36073
## - MVR_PTS 1 185108458 1.2175e+11 36073
## - REVOKED 1 243957432 1.2181e+11 36074
## - BLUEBOOK 1 1302879099 1.2287e+11 36091
##
## Step: AIC=36069.85
## TARGET_AMT ~ KIDSDRIV + AGE + HOMEKIDS + YOJ + TRAVTIME + CAR_USE +
## TIF + RED_CAR + CLM_FREQ + REVOKED + MVR_PTS + CAR_AGE +
## INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - TRAVTIME 1 10583155 1.2158e+11 36068
## - KIDSDRIV 1 12026440 1.2158e+11 36068
## - CAR_USE 1 18142211 1.2159e+11 36068
## - RED_CAR 1 19040049 1.2159e+11 36068
## - YOJ 1 19348550 1.2159e+11 36068
## - INCOME 1 29818379 1.2160e+11 36068
## - TIF 1 33585592 1.2160e+11 36068
## - CLM_FREQ 1 43050354 1.2161e+11 36069
## - AGE 1 64223029 1.2164e+11 36069
## - HOME_VAL 1 65317881 1.2164e+11 36069
## - OLDCLAIM 1 88804959 1.2166e+11 36069
## - HOMEKIDS 1 90944370 1.2166e+11 36069
## - CAR_AGE 1 105327287 1.2168e+11 36070
## <none> 1.2157e+11 36070
## - SEX 1 147371685 1.2172e+11 36070
## - MVR_PTS 1 187176286 1.2176e+11 36071
## - REVOKED 1 245828287 1.2182e+11 36072
## - MSTATUS 1 312899566 1.2188e+11 36073
## - BLUEBOOK 1 1303707132 1.2287e+11 36089
##
## Step: AIC=36068.02
## TARGET_AMT ~ KIDSDRIV + AGE + HOMEKIDS + YOJ + CAR_USE + TIF +
## RED_CAR + CLM_FREQ + REVOKED + MVR_PTS + CAR_AGE + INCOME +
## HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - KIDSDRIV 1 12717116 1.2159e+11 36066
## - CAR_USE 1 15900397 1.2160e+11 36066
## - RED_CAR 1 18818620 1.2160e+11 36066
## - YOJ 1 19663593 1.2160e+11 36066
## - INCOME 1 28657692 1.2161e+11 36066
## - TIF 1 34495010 1.2162e+11 36067
## - CLM_FREQ 1 41430585 1.2162e+11 36067
## - HOME_VAL 1 64787510 1.2165e+11 36067
## - AGE 1 65838971 1.2165e+11 36067
## - OLDCLAIM 1 86104148 1.2167e+11 36067
## - HOMEKIDS 1 90316554 1.2167e+11 36068
## - CAR_AGE 1 103997897 1.2169e+11 36068
## <none> 1.2158e+11 36068
## - SEX 1 148338358 1.2173e+11 36068
## - MVR_PTS 1 188617256 1.2177e+11 36069
## - REVOKED 1 243714639 1.2183e+11 36070
## - MSTATUS 1 309146076 1.2189e+11 36071
## - BLUEBOOK 1 1309357711 1.2289e+11 36088
##
## Step: AIC=36066.23
## TARGET_AMT ~ AGE + HOMEKIDS + YOJ + CAR_USE + TIF + RED_CAR +
## CLM_FREQ + REVOKED + MVR_PTS + CAR_AGE + INCOME + HOME_VAL +
## BLUEBOOK + OLDCLAIM + MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - CAR_USE 1 17681725 1.2161e+11 36065
## - RED_CAR 1 18235722 1.2161e+11 36065
## - YOJ 1 20575176 1.2162e+11 36065
## - INCOME 1 31431047 1.2163e+11 36065
## - TIF 1 34132616 1.2163e+11 36065
## - CLM_FREQ 1 42623742 1.2164e+11 36065
## - AGE 1 56669663 1.2165e+11 36065
## - HOME_VAL 1 64015480 1.2166e+11 36065
## - HOMEKIDS 1 79558260 1.2167e+11 36066
## - OLDCLAIM 1 87579344 1.2168e+11 36066
## - CAR_AGE 1 102810967 1.2170e+11 36066
## <none> 1.2159e+11 36066
## - SEX 1 145934102 1.2174e+11 36067
## - MVR_PTS 1 188017744 1.2178e+11 36067
## - REVOKED 1 250237302 1.2184e+11 36068
## - MSTATUS 1 307680961 1.2190e+11 36069
## - BLUEBOOK 1 1300629748 1.2290e+11 36086
##
## Step: AIC=36064.53
## TARGET_AMT ~ AGE + HOMEKIDS + YOJ + TIF + RED_CAR + CLM_FREQ +
## REVOKED + MVR_PTS + CAR_AGE + INCOME + HOME_VAL + BLUEBOOK +
## OLDCLAIM + MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - RED_CAR 1 18131672 1.2163e+11 36063
## - YOJ 1 18515875 1.2163e+11 36063
## - INCOME 1 28249484 1.2164e+11 36063
## - TIF 1 30953795 1.2164e+11 36063
## - CLM_FREQ 1 40604710 1.2165e+11 36063
## - AGE 1 51155104 1.2166e+11 36063
## - HOME_VAL 1 63614498 1.2168e+11 36064
## - HOMEKIDS 1 75609382 1.2169e+11 36064
## - OLDCLAIM 1 85221119 1.2170e+11 36064
## - CAR_AGE 1 113267333 1.2173e+11 36064
## <none> 1.2161e+11 36065
## - SEX 1 185303260 1.2180e+11 36066
## - MVR_PTS 1 197769471 1.2181e+11 36066
## - REVOKED 1 241532321 1.2185e+11 36067
## - MSTATUS 1 301138160 1.2191e+11 36068
## - BLUEBOOK 1 1430529112 1.2304e+11 36086
##
## Step: AIC=36062.83
## TARGET_AMT ~ AGE + HOMEKIDS + YOJ + TIF + CLM_FREQ + REVOKED +
## MVR_PTS + CAR_AGE + INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM +
## MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - YOJ 1 20029097 1.2165e+11 36061
## - INCOME 1 28847085 1.2166e+11 36061
## - TIF 1 30758533 1.2166e+11 36061
## - CLM_FREQ 1 39971637 1.2167e+11 36061
## - AGE 1 53552250 1.2168e+11 36062
## - HOME_VAL 1 64187132 1.2169e+11 36062
## - HOMEKIDS 1 75837247 1.2171e+11 36062
## - OLDCLAIM 1 82877633 1.2171e+11 36062
## - CAR_AGE 1 115339012 1.2175e+11 36063
## <none> 1.2163e+11 36063
## - MVR_PTS 1 194860176 1.2183e+11 36064
## - SEX 1 208618206 1.2184e+11 36064
## - REVOKED 1 238490978 1.2187e+11 36065
## - MSTATUS 1 302094286 1.2193e+11 36066
## - BLUEBOOK 1 1428900494 1.2306e+11 36084
##
## Step: AIC=36061.16
## TARGET_AMT ~ AGE + HOMEKIDS + TIF + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS +
## SEX
##
## Df Sum of Sq RSS AIC
## - INCOME 1 19115469 1.2167e+11 36059
## - TIF 1 29924316 1.2168e+11 36060
## - CLM_FREQ 1 41351255 1.2169e+11 36060
## - AGE 1 61834474 1.2171e+11 36060
## - HOME_VAL 1 73217972 1.2172e+11 36060
## - OLDCLAIM 1 83923138 1.2173e+11 36061
## - HOMEKIDS 1 89680817 1.2174e+11 36061
## <none> 1.2165e+11 36061
## - CAR_AGE 1 127930245 1.2178e+11 36061
## - MVR_PTS 1 193196473 1.2184e+11 36062
## - SEX 1 213453598 1.2186e+11 36063
## - REVOKED 1 234184361 1.2188e+11 36063
## - MSTATUS 1 294639752 1.2195e+11 36064
## - BLUEBOOK 1 1432597492 1.2308e+11 36083
##
## Step: AIC=36059.47
## TARGET_AMT ~ AGE + HOMEKIDS + TIF + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - TIF 1 28608666 1.2170e+11 36058
## - CLM_FREQ 1 41330543 1.2171e+11 36058
## - HOME_VAL 1 54237900 1.2172e+11 36058
## - AGE 1 59356258 1.2173e+11 36058
## - OLDCLAIM 1 84070404 1.2175e+11 36059
## - HOMEKIDS 1 90047387 1.2176e+11 36059
## <none> 1.2167e+11 36059
## - CAR_AGE 1 180542974 1.2185e+11 36060
## - MVR_PTS 1 193870373 1.2186e+11 36061
## - SEX 1 204643732 1.2187e+11 36061
## - REVOKED 1 235054611 1.2190e+11 36061
## - MSTATUS 1 276135658 1.2195e+11 36062
## - BLUEBOOK 1 1467753477 1.2314e+11 36082
##
## Step: AIC=36057.95
## TARGET_AMT ~ AGE + HOMEKIDS + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - CLM_FREQ 1 44067998 1.2174e+11 36057
## - HOME_VAL 1 55524616 1.2175e+11 36057
## - AGE 1 59659792 1.2176e+11 36057
## - OLDCLAIM 1 84734409 1.2178e+11 36057
## - HOMEKIDS 1 90426149 1.2179e+11 36057
## <none> 1.2170e+11 36058
## - CAR_AGE 1 177870390 1.2188e+11 36059
## - MVR_PTS 1 200822202 1.2190e+11 36059
## - SEX 1 205447327 1.2190e+11 36059
## - REVOKED 1 234411359 1.2193e+11 36060
## - MSTATUS 1 270025675 1.2197e+11 36060
## - BLUEBOOK 1 1466813096 1.2316e+11 36080
##
## Step: AIC=36056.67
## TARGET_AMT ~ AGE + HOMEKIDS + REVOKED + MVR_PTS + CAR_AGE + HOME_VAL +
## BLUEBOOK + OLDCLAIM + MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - OLDCLAIM 1 48636304 1.2179e+11 36055
## - HOME_VAL 1 55667628 1.2180e+11 36056
## - AGE 1 58174981 1.2180e+11 36056
## - HOMEKIDS 1 91125091 1.2183e+11 36056
## <none> 1.2174e+11 36057
## - MVR_PTS 1 167280814 1.2191e+11 36057
## - CAR_AGE 1 188399330 1.2193e+11 36058
## - REVOKED 1 198124852 1.2194e+11 36058
## - SEX 1 203997706 1.2195e+11 36058
## - MSTATUS 1 269490060 1.2201e+11 36059
## - BLUEBOOK 1 1471542457 1.2321e+11 36079
##
## Step: AIC=36055.48
## TARGET_AMT ~ AGE + HOMEKIDS + REVOKED + MVR_PTS + CAR_AGE + HOME_VAL +
## BLUEBOOK + MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - HOME_VAL 1 58740059 1.2185e+11 36054
## - AGE 1 59261910 1.2185e+11 36054
## - HOMEKIDS 1 88684255 1.2188e+11 36055
## <none> 1.2179e+11 36055
## - REVOKED 1 150394814 1.2194e+11 36056
## - CAR_AGE 1 184351389 1.2198e+11 36057
## - SEX 1 197901853 1.2199e+11 36057
## - MVR_PTS 1 212421634 1.2200e+11 36057
## - MSTATUS 1 267708130 1.2206e+11 36058
## - BLUEBOOK 1 1452132145 1.2324e+11 36077
##
## Step: AIC=36054.45
## TARGET_AMT ~ AGE + HOMEKIDS + REVOKED + MVR_PTS + CAR_AGE + BLUEBOOK +
## MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - AGE 1 71370786 1.2192e+11 36054
## - HOMEKIDS 1 83747039 1.2193e+11 36054
## <none> 1.2185e+11 36054
## - CAR_AGE 1 154513388 1.2200e+11 36055
## - REVOKED 1 155653552 1.2201e+11 36055
## - MVR_PTS 1 203955706 1.2205e+11 36056
## - SEX 1 208593868 1.2206e+11 36056
## - MSTATUS 1 209106117 1.2206e+11 36056
## - BLUEBOOK 1 1645147417 1.2349e+11 36079
##
## Step: AIC=36053.62
## TARGET_AMT ~ HOMEKIDS + REVOKED + MVR_PTS + CAR_AGE + BLUEBOOK +
## MSTATUS + SEX
##
## Df Sum of Sq RSS AIC
## - HOMEKIDS 1 38484030 1.2196e+11 36052
## <none> 1.2192e+11 36054
## - CAR_AGE 1 131131760 1.2205e+11 36054
## - REVOKED 1 148060934 1.2207e+11 36054
## - MSTATUS 1 175086472 1.2210e+11 36055
## - SEX 1 202608661 1.2212e+11 36055
## - MVR_PTS 1 202828770 1.2212e+11 36055
## - BLUEBOOK 1 1746551592 1.2367e+11 36080
##
## Step: AIC=36052.26
## TARGET_AMT ~ REVOKED + MVR_PTS + CAR_AGE + BLUEBOOK + MSTATUS +
## SEX
##
## Df Sum of Sq RSS AIC
## <none> 1.2196e+11 36052
## - CAR_AGE 1 140440225 1.2210e+11 36053
## - REVOKED 1 141378251 1.2210e+11 36053
## - MSTATUS 1 164261705 1.2212e+11 36053
## - SEX 1 188329377 1.2215e+11 36053
## - MVR_PTS 1 210544699 1.2217e+11 36054
## - BLUEBOOK 1 1724209476 1.2368e+11 36078##
## Call:
## lm(formula = TARGET_AMT ~ REVOKED + MVR_PTS + CAR_AGE + BLUEBOOK +
## MSTATUS + SEX, data = df_lm)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8263 -3162 -1574 325 100465
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4281.91344 503.98221 8.496 < 2e-16 ***
## REVOKEDYes -656.16299 430.50600 -1.524 0.1276
## MVR_PTS 125.73815 67.60109 1.860 0.0630 .
## CAR_AGE -48.79606 32.12165 -1.519 0.1289
## BLUEBOOK 0.11376 0.02137 5.323 1.14e-07 ***
## MSTATUSYes -573.12750 348.85252 -1.643 0.1006
## SEXM 618.26245 351.45734 1.759 0.0787 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7801 on 2004 degrees of freedom
## (142 observations deleted due to missingness)
## Multiple R-squared: 0.02061, Adjusted R-squared: 0.01767
## F-statistic: 7.027 on 6 and 2004 DF, p-value: 2.043e-07Model 3: BoxCox imputation
##
## Call:
## lm(formula = TARGET_AMT ~ KIDSDRIV + AGE + HOMEKIDS + I(YOJ^1.6) +
## PARENT1 + I(TRAVTIME^0.7) + CAR_USE + I(TIF^0.2) + RED_CAR +
## CLM_FREQ + REVOKED + MVR_PTS + I(CAR_AGE^0.5) + I(INCOME^0.4) +
## HOME_VAL + I(BLUEBOOK^0.5) + OLDCLAIM + MSTATUS + SEX + EDUCATION +
## JOB + CAR_TYPE + URBANICITY, data = df_lm)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8792 -3250 -1499 530 99271
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.950e+03 2.476e+03 0.788 0.4310
## KIDSDRIV -1.437e+02 3.390e+02 -0.424 0.6717
## AGE 1.214e+01 2.265e+01 0.536 0.5921
## HOMEKIDS 2.291e+02 2.205e+02 1.039 0.2989
## I(YOJ^1.6) 1.451e+00 9.802e+00 0.148 0.8823
## PARENT1Yes 1.700e+02 6.172e+02 0.276 0.7830
## I(TRAVTIME^0.7) 1.111e+01 4.701e+01 0.236 0.8132
## CAR_USEPrivate -4.413e+02 5.489e+02 -0.804 0.4214
## I(TIF^0.2) -4.381e+02 7.321e+02 -0.598 0.5497
## RED_CARyes -2.595e+02 5.217e+02 -0.497 0.6190
## CLM_FREQ -1.520e+02 1.663e+02 -0.914 0.3610
## REVOKEDYes -1.167e+03 5.430e+02 -2.149 0.0317 *
## MVR_PTS 1.135e+02 7.243e+01 1.566 0.1174
## I(CAR_AGE^0.5) -3.511e+02 2.122e+02 -1.655 0.0982 .
## I(INCOME^0.4) -2.820e+00 1.120e+01 -0.252 0.8012
## HOME_VAL 1.132e-03 2.066e-03 0.548 0.5837
## I(BLUEBOOK^0.5) 2.917e+01 7.245e+00 4.026 5.89e-05 ***
## OLDCLAIM 3.307e-02 2.366e-02 1.397 0.1624
## MSTATUSYes -7.339e+02 5.226e+02 -1.404 0.1604
## SEXM 1.386e+03 6.789e+02 2.042 0.0413 *
## EDUCATIONBachelors 1.807e+01 6.843e+02 0.026 0.9789
## EDUCATIONHigh School -6.488e+02 5.425e+02 -1.196 0.2319
## EDUCATIONMasters 4.820e+02 1.130e+03 0.426 0.6699
## EDUCATIONPhD 1.746e+03 1.349e+03 1.294 0.1957
## JOBBlue Collar 7.549e+02 1.200e+03 0.629 0.5294
## JOBClerical 5.742e+02 1.255e+03 0.457 0.6474
## JOBDoctor -2.158e+03 1.814e+03 -1.189 0.2345
## JOBHome Maker 4.477e+02 1.391e+03 0.322 0.7477
## JOBLawyer 4.032e+02 1.074e+03 0.375 0.7075
## JOBManager -7.432e+02 1.129e+03 -0.659 0.5103
## JOBProfessional 1.439e+03 1.179e+03 1.221 0.2223
## JOBStudent 4.161e+02 1.411e+03 0.295 0.7681
## CAR_TYPEPanel Truck -3.759e+02 9.639e+02 -0.390 0.6966
## CAR_TYPEPickup -1.729e+02 6.290e+02 -0.275 0.7835
## CAR_TYPESports Car 1.111e+03 7.840e+02 1.417 0.1567
## CAR_TYPESUV 9.021e+02 6.886e+02 1.310 0.1903
## CAR_TYPEVan 2.934e+02 8.101e+02 0.362 0.7172
## URBANICITYHighly Urban/ Urban 9.856e+01 7.962e+02 0.124 0.9015
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7821 on 1972 degrees of freedom
## (143 observations deleted due to missingness)
## Multiple R-squared: 0.03108, Adjusted R-squared: 0.0129
## F-statistic: 1.71 on 37 and 1972 DF, p-value: 0.00508Residual analysis…
Logistic Regression Models
Model 1: Mean full model
Let build the first full model for logistiv regression…
##
## Call:
## glm(formula = TARGET_FLAG ~ ., family = "binomial", data = df_rm)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.5654 -0.7168 -0.3972 0.6148 3.1535
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.994e+00 3.520e-01 -8.506 < 2e-16 ***
## KIDSDRIV 3.455e-01 6.381e-02 5.414 6.16e-08 ***
## AGE 3.193e-04 4.145e-03 0.077 0.938603
## HOMEKIDS 6.304e-02 3.822e-02 1.649 0.099118 .
## YOJ -1.136e-02 8.872e-03 -1.280 0.200450
## PARENT1Yes 3.853e-01 1.131e-01 3.406 0.000659 ***
## TRAVTIME 1.492e-02 1.953e-03 7.641 2.16e-14 ***
## CAR_USEPrivate -7.534e-01 9.459e-02 -7.965 1.65e-15 ***
## TIF -5.512e-02 7.590e-03 -7.261 3.83e-13 ***
## RED_CARyes 1.800e-03 8.927e-02 0.020 0.983911
## CLM_FREQ 2.025e-01 2.938e-02 6.892 5.51e-12 ***
## REVOKEDYes 8.804e-01 9.439e-02 9.327 < 2e-16 ***
## MVR_PTS 1.142e-01 1.405e-02 8.132 4.22e-16 ***
## CAR_AGE -4.559e-03 7.797e-03 -0.585 0.558745
## INCOME -3.107e-06 1.116e-06 -2.783 0.005386 **
## HOME_VAL -1.290e-06 3.525e-07 -3.658 0.000254 ***
## BLUEBOOK -2.147e-05 5.439e-06 -3.949 7.86e-05 ***
## OLDCLAIM -1.288e-05 4.011e-06 -3.211 0.001324 **
## MSTATUSYes -4.902e-01 8.656e-02 -5.663 1.49e-08 ***
## SEXM 8.549e-02 1.154e-01 0.741 0.458957
## EDUCATIONBachelors -3.626e-01 1.198e-01 -3.027 0.002470 **
## EDUCATIONHigh School 3.528e-02 9.786e-02 0.361 0.718470
## EDUCATIONMasters -2.129e-01 1.865e-01 -1.141 0.253692
## EDUCATIONPhD -1.214e-01 2.231e-01 -0.544 0.586367
## JOBBlue Collar 3.198e-01 1.922e-01 1.664 0.096189 .
## JOBClerical 4.362e-01 2.034e-01 2.144 0.031997 *
## JOBDoctor -3.528e-01 2.716e-01 -1.299 0.193892
## JOBHome Maker 2.764e-01 2.176e-01 1.270 0.204072
## JOBLawyer 1.035e-01 1.749e-01 0.592 0.554008
## JOBManager -6.151e-01 1.784e-01 -3.449 0.000563 ***
## JOBProfessional 1.439e-01 1.842e-01 0.781 0.434798
## JOBStudent 1.991e-01 2.226e-01 0.894 0.371160
## CAR_TYPEPanel Truck 6.109e-01 1.669e-01 3.661 0.000251 ***
## CAR_TYPEPickup 5.267e-01 1.041e-01 5.058 4.24e-07 ***
## CAR_TYPESports Car 9.979e-01 1.341e-01 7.440 1.01e-13 ***
## CAR_TYPESUV 7.535e-01 1.147e-01 6.570 5.03e-11 ***
## CAR_TYPEVan 5.872e-01 1.304e-01 4.503 6.71e-06 ***
## URBANICITYHighly Urban/ Urban 2.373e+00 1.164e-01 20.385 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 8814.1 on 7650 degrees of freedom
## Residual deviance: 6831.7 on 7613 degrees of freedom
## (510 observations deleted due to missingness)
## AIC: 6907.7
##
## Number of Fisher Scoring iterations: 5Confusion matrix and the curve…
probabilities <- predict(rm_model1, df_rm, type = "response")
predicted1.classes <- ifelse(probabilities > 0.5, 1, 0)
df_rm$pred1.class <- predicted1.classes
table("Predictions" = df_rm$pred1.class, "Actual" = df_rm$TARGET_FLAG)## Actual
## Predictions 0 1
## 0 5216 1172
## 1 424 839## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 5216 1172
## 1 424 839
##
## Accuracy : 0.7914
## 95% CI : (0.7821, 0.8005)
## No Information Rate : 0.7372
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.3885
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.9248
## Specificity : 0.4172
## Pos Pred Value : 0.8165
## Neg Pred Value : 0.6643
## Prevalence : 0.7372
## Detection Rate : 0.6817
## Detection Prevalence : 0.8349
## Balanced Accuracy : 0.6710
##
## 'Positive' Class : 0
## 
Model 2: Random forest
Logistic regression with Random forest…
##
## Call:
## randomForest(formula = factor(TARGET_FLAG) ~ ., data = rf_train, na.action = na.omit)
## Type of random forest: classification
## Number of trees: 500
## No. of variables tried at each split: 4
##
## OOB estimate of error rate: 21.5%
## Confusion matrix:
## 0 1 class.error
## 0 4202 293 0.06518354
## 1 1023 604 0.62876460
Confusion matrix…
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 1070 243
## 1 75 141
##
## Accuracy : 0.792
## 95% CI : (0.7708, 0.8121)
## No Information Rate : 0.7489
## P-Value [Acc > NIR] : 4.115e-05
##
## Kappa : 0.353
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.36719
## Specificity : 0.93450
## Pos Pred Value : 0.65278
## Neg Pred Value : 0.81493
## Prevalence : 0.25114
## Detection Rate : 0.09222
## Detection Prevalence : 0.14127
## Balanced Accuracy : 0.65084
##
## 'Positive' Class : 1
## Model 3: Stepwise
The stepwise model…
## Start: AIC=5564.81
## TARGET_FLAG ~ KIDSDRIV + AGE + HOMEKIDS + YOJ + PARENT1 + TRAVTIME +
## CAR_USE + TIF + RED_CAR + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS +
## SEX + EDUCATION + JOB + CAR_TYPE + URBANICITY
##
## Df Deviance AIC
## - AGE 1 5488.8 5562.8
## - RED_CAR 1 5488.8 5562.8
## - SEX 1 5489.2 5563.2
## - YOJ 1 5489.5 5563.5
## - CAR_AGE 1 5489.6 5563.6
## <none> 5488.8 5564.8
## - HOMEKIDS 1 5491.2 5565.2
## - OLDCLAIM 1 5495.7 5569.7
## - INCOME 1 5499.0 5573.0
## - HOME_VAL 1 5499.5 5573.5
## - EDUCATION 4 5506.2 5574.2
## - PARENT1 1 5501.9 5575.9
## - BLUEBOOK 1 5507.1 5581.1
## - KIDSDRIV 1 5509.5 5583.5
## - MSTATUS 1 5510.6 5584.6
## - CLM_FREQ 1 5521.8 5595.8
## - JOB 8 5536.0 5596.0
## - TRAVTIME 1 5533.2 5607.2
## - CAR_TYPE 5 5542.5 5608.5
## - CAR_USE 1 5538.7 5612.7
## - MVR_PTS 1 5539.6 5613.6
## - TIF 1 5544.1 5618.1
## - REVOKED 1 5547.4 5621.4
## - URBANICITY 1 5987.1 6061.1
##
## Step: AIC=5562.81
## TARGET_FLAG ~ KIDSDRIV + HOMEKIDS + YOJ + PARENT1 + TRAVTIME +
## CAR_USE + TIF + RED_CAR + CLM_FREQ + REVOKED + MVR_PTS +
## CAR_AGE + INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS +
## SEX + EDUCATION + JOB + CAR_TYPE + URBANICITY
##
## Df Deviance AIC
## - RED_CAR 1 5488.8 5560.8
## - SEX 1 5489.2 5561.2
## - YOJ 1 5489.5 5561.5
## - CAR_AGE 1 5489.6 5561.6
## <none> 5488.8 5562.8
## - HOMEKIDS 1 5491.6 5563.6
## - OLDCLAIM 1 5495.7 5567.7
## - INCOME 1 5499.0 5571.0
## - HOME_VAL 1 5499.5 5571.5
## - EDUCATION 4 5506.2 5572.2
## - PARENT1 1 5502.1 5574.1
## - BLUEBOOK 1 5507.6 5579.6
## - KIDSDRIV 1 5510.1 5582.1
## - MSTATUS 1 5510.6 5582.6
## - CLM_FREQ 1 5521.8 5593.8
## - JOB 8 5536.3 5594.3
## - TRAVTIME 1 5533.2 5605.2
## - CAR_TYPE 5 5542.7 5606.7
## - CAR_USE 1 5538.7 5610.7
## - MVR_PTS 1 5539.7 5611.7
## - TIF 1 5544.1 5616.1
## - REVOKED 1 5547.4 5619.4
## - URBANICITY 1 5987.4 6059.4
##
## Step: AIC=5560.82
## TARGET_FLAG ~ KIDSDRIV + HOMEKIDS + YOJ + PARENT1 + TRAVTIME +
## CAR_USE + TIF + CLM_FREQ + REVOKED + MVR_PTS + CAR_AGE +
## INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS + SEX +
## EDUCATION + JOB + CAR_TYPE + URBANICITY
##
## Df Deviance AIC
## - SEX 1 5489.3 5559.3
## - YOJ 1 5489.5 5559.5
## - CAR_AGE 1 5489.6 5559.6
## <none> 5488.8 5560.8
## - HOMEKIDS 1 5491.6 5561.6
## - OLDCLAIM 1 5495.7 5565.7
## - INCOME 1 5499.0 5569.0
## - HOME_VAL 1 5499.5 5569.5
## - EDUCATION 4 5506.2 5570.2
## - PARENT1 1 5502.1 5572.1
## - BLUEBOOK 1 5507.6 5577.6
## - KIDSDRIV 1 5510.1 5580.1
## - MSTATUS 1 5510.6 5580.6
## - CLM_FREQ 1 5521.8 5591.8
## - JOB 8 5536.3 5592.3
## - TRAVTIME 1 5533.2 5603.2
## - CAR_TYPE 5 5542.7 5604.7
## - CAR_USE 1 5538.8 5608.8
## - MVR_PTS 1 5539.7 5609.7
## - TIF 1 5544.1 5614.1
## - REVOKED 1 5547.4 5617.4
## - URBANICITY 1 5987.4 6057.4
##
## Step: AIC=5559.31
## TARGET_FLAG ~ KIDSDRIV + HOMEKIDS + YOJ + PARENT1 + TRAVTIME +
## CAR_USE + TIF + CLM_FREQ + REVOKED + MVR_PTS + CAR_AGE +
## INCOME + HOME_VAL + BLUEBOOK + OLDCLAIM + MSTATUS + EDUCATION +
## JOB + CAR_TYPE + URBANICITY
##
## Df Deviance AIC
## - YOJ 1 5490.0 5558.0
## - CAR_AGE 1 5490.1 5558.1
## <none> 5489.3 5559.3
## - HOMEKIDS 1 5492.0 5560.0
## - OLDCLAIM 1 5496.2 5564.2
## - INCOME 1 5499.6 5567.6
## - HOME_VAL 1 5499.9 5567.9
## - EDUCATION 4 5506.6 5568.6
## - PARENT1 1 5502.6 5570.6
## - KIDSDRIV 1 5510.7 5578.7
## - MSTATUS 1 5511.1 5579.1
## - BLUEBOOK 1 5514.9 5582.9
## - CLM_FREQ 1 5522.5 5590.5
## - JOB 8 5536.5 5590.5
## - TRAVTIME 1 5533.8 5601.8
## - CAR_USE 1 5539.2 5607.2
## - MVR_PTS 1 5540.2 5608.2
## - CAR_TYPE 5 5549.2 5609.2
## - TIF 1 5544.4 5612.4
## - REVOKED 1 5548.1 5616.1
## - URBANICITY 1 5988.0 6056.0
##
## Step: AIC=5557.98
## TARGET_FLAG ~ KIDSDRIV + HOMEKIDS + PARENT1 + TRAVTIME + CAR_USE +
## TIF + CLM_FREQ + REVOKED + MVR_PTS + CAR_AGE + INCOME + HOME_VAL +
## BLUEBOOK + OLDCLAIM + MSTATUS + EDUCATION + JOB + CAR_TYPE +
## URBANICITY
##
## Df Deviance AIC
## - CAR_AGE 1 5490.8 5556.8
## <none> 5490.0 5558.0
## - HOMEKIDS 1 5492.3 5558.3
## - OLDCLAIM 1 5497.0 5563.0
## - HOME_VAL 1 5500.7 5566.7
## - INCOME 1 5500.7 5566.7
## - EDUCATION 4 5507.2 5567.2
## - PARENT1 1 5503.5 5569.5
## - KIDSDRIV 1 5511.6 5577.6
## - MSTATUS 1 5512.6 5578.6
## - BLUEBOOK 1 5516.1 5582.1
## - JOB 8 5536.9 5588.9
## - CLM_FREQ 1 5523.2 5589.2
## - TRAVTIME 1 5534.4 5600.4
## - CAR_USE 1 5540.3 5606.3
## - MVR_PTS 1 5541.6 5607.6
## - CAR_TYPE 5 5550.0 5608.0
## - TIF 1 5545.4 5611.4
## - REVOKED 1 5548.8 5614.8
## - URBANICITY 1 5988.3 6054.3
##
## Step: AIC=5556.8
## TARGET_FLAG ~ KIDSDRIV + HOMEKIDS + PARENT1 + TRAVTIME + CAR_USE +
## TIF + CLM_FREQ + REVOKED + MVR_PTS + INCOME + HOME_VAL +
## BLUEBOOK + OLDCLAIM + MSTATUS + EDUCATION + JOB + CAR_TYPE +
## URBANICITY
##
## Df Deviance AIC
## <none> 5490.8 5556.8
## - HOMEKIDS 1 5493.2 5557.2
## - OLDCLAIM 1 5497.9 5561.9
## - HOME_VAL 1 5501.3 5565.3
## - INCOME 1 5501.7 5565.7
## - PARENT1 1 5504.2 5568.2
## - EDUCATION 4 5514.1 5572.1
## - KIDSDRIV 1 5512.5 5576.5
## - MSTATUS 1 5513.5 5577.5
## - BLUEBOOK 1 5516.9 5580.9
## - JOB 8 5537.7 5587.7
## - CLM_FREQ 1 5523.8 5587.8
## - TRAVTIME 1 5535.1 5599.1
## - CAR_USE 1 5540.9 5604.9
## - MVR_PTS 1 5542.4 5606.4
## - CAR_TYPE 5 5551.2 5607.2
## - TIF 1 5546.5 5610.5
## - REVOKED 1 5549.7 5613.7
## - URBANICITY 1 5989.6 6053.6##
## Call:
## glm(formula = TARGET_FLAG ~ KIDSDRIV + HOMEKIDS + PARENT1 + TRAVTIME +
## CAR_USE + TIF + CLM_FREQ + REVOKED + MVR_PTS + INCOME + HOME_VAL +
## BLUEBOOK + OLDCLAIM + MSTATUS + EDUCATION + JOB + CAR_TYPE +
## URBANICITY, family = "binomial", data = no_na_df)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.5388 -0.7167 -0.3954 0.6413 3.1311
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.735e+00 3.204e-01 -8.538 < 2e-16 ***
## KIDSDRIV 3.281e-01 7.042e-02 4.660 3.17e-06 ***
## HOMEKIDS 5.966e-02 3.870e-02 1.542 0.123192
## PARENT1Yes 4.582e-01 1.252e-01 3.660 0.000252 ***
## TRAVTIME 1.451e-02 2.185e-03 6.640 3.14e-11 ***
## CAR_USEPrivate -7.386e-01 1.051e-01 -7.027 2.11e-12 ***
## TIF -6.213e-02 8.506e-03 -7.304 2.79e-13 ***
## CLM_FREQ 1.881e-01 3.251e-02 5.787 7.18e-09 ***
## REVOKEDYes 8.186e-01 1.057e-01 7.746 9.48e-15 ***
## MVR_PTS 1.127e-01 1.576e-02 7.151 8.63e-13 ***
## INCOME -4.047e-06 1.237e-06 -3.271 0.001073 **
## HOME_VAL -1.276e-06 3.946e-07 -3.234 0.001222 **
## BLUEBOOK -2.765e-05 5.487e-06 -5.040 4.66e-07 ***
## OLDCLAIM -1.173e-05 4.452e-06 -2.636 0.008397 **
## MSTATUSYes -4.614e-01 9.631e-02 -4.791 1.66e-06 ***
## EDUCATIONBachelors -3.685e-01 1.247e-01 -2.955 0.003129 **
## EDUCATIONHigh School 9.227e-02 1.087e-01 0.849 0.395887
## EDUCATIONMasters -2.755e-01 1.862e-01 -1.480 0.138960
## EDUCATIONPhD -2.494e-01 2.316e-01 -1.077 0.281630
## JOBBlue Collar 2.396e-01 2.167e-01 1.106 0.268822
## JOBClerical 2.895e-01 2.291e-01 1.264 0.206303
## JOBDoctor -2.506e-01 3.021e-01 -0.830 0.406734
## JOBHome Maker 1.716e-01 2.381e-01 0.721 0.470913
## JOBLawyer 1.536e-02 1.950e-01 0.079 0.937207
## JOBManager -6.526e-01 2.010e-01 -3.247 0.001165 **
## JOBProfessional 2.182e-02 2.072e-01 0.105 0.916118
## JOBStudent 6.000e-02 2.455e-01 0.244 0.806933
## CAR_TYPEPanel Truck 6.856e-01 1.733e-01 3.957 7.59e-05 ***
## CAR_TYPEPickup 4.974e-01 1.159e-01 4.292 1.77e-05 ***
## CAR_TYPESports Car 8.126e-01 1.245e-01 6.526 6.77e-11 ***
## CAR_TYPESUV 5.899e-01 9.799e-02 6.020 1.74e-09 ***
## CAR_TYPEVan 5.494e-01 1.421e-01 3.867 0.000110 ***
## URBANICITYHighly Urban/ Urban 2.391e+00 1.285e-01 18.609 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 7089.3 on 6121 degrees of freedom
## Residual deviance: 5490.8 on 6089 degrees of freedom
## AIC: 5556.8
##
## Number of Fisher Scoring iterations: 5Confusion matrix and the curve…
## Actual
## Predictions 0 1
## 0 1122 249
## 1 91 170## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 1122 249
## 1 91 170
##
## Accuracy : 0.7917
## 95% CI : (0.7711, 0.8111)
## No Information Rate : 0.7433
## P-Value [Acc > NIR] : 2.754e-06
##
## Kappa : 0.3773
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.4057
## Specificity : 0.9250
## Pos Pred Value : 0.6513
## Neg Pred Value : 0.8184
## Prevalence : 0.2567
## Detection Rate : 0.1042
## Detection Prevalence : 0.1599
## Balanced Accuracy : 0.6654
##
## 'Positive' Class : 1
## 
Select Models
We will use the Stepwise regression models for both questions, as the logistic stepwise model was the most accurate, had the highest sensitivity, and was the least complex. The stepwise linear model also had a higher adjusted R^2 value, and a smaller p-value. Thus, these should be our best bet in imputing the target values in the evaluation dataset.
Does the person crash the car?
The following shows if a person crash his or her car…
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
## 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1
## 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
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## 0 0 1 1 0 0 0 0 1 0 1 0 0 0 0 0
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## 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0
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## 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 1
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## 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0
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## 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1
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## 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1
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## 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0
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## 0 0 0 0 1 1 1 0 0 0 0 0 1 0 0 0
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## 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 1
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## 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0
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## 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
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## 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0
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## 0 0 1 1 1 0 0 1 1 0 0 0 0 0 1 0
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## 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
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## 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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## 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
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## 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0
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## 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0
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## 1 1 0 0 0 0 0 0 0 1 0 1 1 1 0 0
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## 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0
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## 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0
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## 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0
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## 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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## 0 0 0 1 1 1 0 0 0 0 0 1 0 1 0 0
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## 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
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## 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0
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## 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1
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## 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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## 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0
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## 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0
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## 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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## 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0
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## 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0
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## 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0
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## 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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## 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## 1489 1490 1491 1492 1493 1494 1495 1496 1497 1498 1499 1500 1501 1502 1503 1504
## 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1
## 1505 1506 1507 1508 1509 1510 1511 1512 1513 1514 1515 1516 1517 1518 1519 1520
## 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 1521 1522 1523 1524 1525 1526 1527 1528 1529 1530 1531 1532 1533 1534 1535 1536
## 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
## 1537 1538 1539 1540 1541 1542 1543 1544 1545 1546 1547 1548 1549 1550 1551 1552
## 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0
## 1553 1554 1555 1556 1557 1558 1559 1560 1561 1562 1563 1564 1565 1566 1567 1568
## 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## 1569 1570 1571 1572 1573 1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584
## 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600
## 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
## 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616
## 1 0 0 1 0 1 0 0 0 1 0 0 0 1 0 1
## 1617 1618 1619 1620 1621 1622 1623 1624 1625 1626 1627 1628 1629 1630 1631 1632
## 0 1 0 0 1 0 1 0 0 0 0 0 0 1 0 1
## 1633 1634 1635 1636 1637 1638 1639 1640 1641 1642 1643 1644 1645 1646 1647 1648
## 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## 1649 1650 1651 1652 1653 1654 1655 1656 1657 1658 1659 1660 1661 1662 1663 1664
## 0 1 0 0 0 0 1 0 0 0 0 0 1 1 1 1
## 1665 1666 1667 1668 1669 1670 1671 1672 1673 1674 1675 1676 1677 1678 1679 1680
## 1 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0
## 1681 1682 1683 1684 1685 1686 1687 1688 1689 1690 1691 1692 1693 1694 1695 1696
## 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1
## 1697 1698 1699 1700 1701 1702 1703 1704 1705 1706 1707 1708 1709 1710 1711 1712
## 0 1 1 0 0 0 0 0 0 0 1 0 1 0 0 0
## 1713 1714 1715 1716 1717 1718 1719 1720 1721 1722 1723 1724 1725 1726 1727 1728
## 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 1729 1730 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744
## 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760
## 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
## 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776
## 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0
## 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792
## 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0
## 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808
## 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1
## 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824
## 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840
## 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1
## 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856
## 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872
## 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888
## 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904
## 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920
## 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936
## 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952
## 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968
## 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984
## 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
## 0 0 0 0 0 0 0 1 1 1 0 0 0 1 0 0
## 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
## 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0
## 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032
## 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0
## 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048
## 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1
## 2049 2050 2051 2052 2053 2054 2055 2056 2057 2058 2059 2060 2061 2062 2063 2064
## 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## 2065 2066 2067 2068 2069 2070 2071 2072 2073 2074 2075 2076 2077 2078 2079 2080
## 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 1
## 2081 2082 2083 2084 2085 2086 2087 2088 2089 2090 2091 2092 2093 2094 2095 2096
## 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1
## 2097 2098 2099 2100 2101 2102 2103 2104 2105 2106 2107 2108 2109 2110 2111 2112
## 0 0 1 1 1 0 1 0 0 0 1 0 0 0 1 0
## 2113 2114 2115 2116 2117 2118 2119 2120 2121 2122 2123 2124 2125 2126 2127 2128
## 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0
## 2129 2130 2131 2132 2133 2134 2135 2136 2137 2138 2139 2140 2141
## 0 0 0 0 0 0 0 0 0 0 0 0 0What’s the pay off?
The following shows the pay off for the person who has a crash car…
## 1 2 3 4 5 6 7 8
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 9 10 11 12 13 14 15 16
## 0.000 0.000 0.000 5475.670 NA 0.000 0.000 5696.563
## 17 18 19 20 21 22 23 24
## NA 0.000 4005.702 0.000 0.000 0.000 0.000 0.000
## 25 26 27 28 29 30 31 32
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 33 34 35 36 37 38 39 40
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 5773.914
## 41 42 43 44 45 46 47 48
## 0.000 5222.274 0.000 6895.830 0.000 0.000 0.000 0.000
## 49 50 51 52 53 54 55 56
## 0.000 4122.707 0.000 0.000 6354.033 0.000 0.000 0.000
## 57 58 59 60 61 62 63 64
## 0.000 0.000 0.000 3956.597 0.000 0.000 0.000 0.000
## 65 66 67 68 69 70 71 72
## 0.000 0.000 5079.031 7313.395 0.000 0.000 0.000 0.000
## 73 74 75 76 77 78 79 80
## 5291.526 0.000 5617.353 0.000 0.000 0.000 0.000 0.000
## 81 82 83 84 85 86 87 88
## 4258.968 0.000 0.000 0.000 0.000 6707.825 0.000 0.000
## 89 90 91 92 93 94 95 96
## 0.000 6004.846 0.000 0.000 0.000 0.000 0.000 0.000
## 97 98 99 100 101 102 103 104
## 0.000 0.000 0.000 0.000 0.000 6769.367 6191.289 6218.239
## 105 106 107 108 109 110 111 112
## 0.000 0.000 0.000 0.000 0.000 0.000 5465.364 0.000
## 113 114 115 116 117 118 119 120
## 0.000 0.000 5368.212 0.000 0.000 5420.656 3319.370 0.000
## 121 122 123 124 125 126 127 128
## 0.000 5301.919 4497.096 0.000 0.000 0.000 0.000 0.000
## 129 130 131 132 133 134 135 136
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 137 138 139 140 141 142 143 144
## 6802.093 6829.302 0.000 0.000 0.000 5537.473 0.000 0.000
## 145 146 147 148 149 150 151 152
## 0.000 4494.962 0.000 0.000 0.000 0.000 6005.710 0.000
## 153 154 155 156 157 158 159 160
## 6369.258 0.000 0.000 0.000 0.000 0.000 5348.406 5846.070
## 161 162 163 164 165 166 167 168
## 0.000 0.000 0.000 0.000 7559.370 0.000 0.000 0.000
## 169 170 171 172 173 174 175 176
## 0.000 0.000 0.000 7417.136 0.000 0.000 0.000 0.000
## 177 178 179 180 181 182 183 184
## 8473.842 5261.994 7898.267 4553.929 6200.101 0.000 0.000 0.000
## 185 186 187 188 189 190 191 192
## 0.000 0.000 0.000 0.000 0.000 0.000 4548.520 4814.371
## 193 194 195 196 197 198 199 200
## 0.000 0.000 0.000 4972.555 0.000 0.000 0.000 0.000
## 201 202 203 204 205 206 207 208
## 0.000 0.000 0.000 0.000 0.000 0.000 5968.634 0.000
## 209 210 211 212 213 214 215 216
## 0.000 0.000 0.000 0.000 5545.745 0.000 0.000 0.000
## 217 218 219 220 221 222 223 224
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 225 226 227 228 229 230 231 232
## 0.000 0.000 5783.903 0.000 0.000 0.000 0.000 0.000
## 233 234 235 236 237 238 239 240
## 7067.620 0.000 0.000 0.000 0.000 0.000 0.000 5629.963
## 241 242 243 244 245 246 247 248
## 0.000 0.000 6355.952 0.000 0.000 0.000 0.000 0.000
## 249 250 251 252 253 254 255 256
## 0.000 5206.449 4770.072 5120.150 0.000 0.000 0.000 0.000
## 257 258 259 260 261 262 263 264
## 0.000 0.000 4650.007 0.000 0.000 0.000 0.000 0.000
## 265 266 267 268 269 270 271 272
## 0.000 0.000 0.000 0.000 6977.377 0.000 5488.436 0.000
## 273 274 275 276 277 278 279 280
## 0.000 0.000 0.000 0.000 6451.459 0.000 0.000 0.000
## 281 282 283 284 285 286 287 288
## 0.000 0.000 0.000 0.000 0.000 4902.137 0.000 0.000
## 289 290 291 292 293 294 295 296
## 4036.865 5176.608 0.000 0.000 0.000 0.000 0.000 0.000
## 297 298 299 300 301 302 303 304
## 0.000 6578.373 0.000 0.000 0.000 0.000 0.000 0.000
## 305 306 307 308 309 310 311 312
## 0.000 0.000 0.000 0.000 0.000 0.000 7210.489 0.000
## 313 314 315 316 317 318 319 320
## 0.000 5813.319 0.000 0.000 0.000 0.000 5642.683 0.000
## 321 322 323 324 325 326 327 328
## 0.000 5232.695 0.000 0.000 5213.844 0.000 5652.385 0.000
## 329 330 331 332 333 334 335 336
## 0.000 0.000 0.000 0.000 5111.822 0.000 0.000 0.000
## 337 338 339 340 341 342 343 344
## 0.000 5345.916 0.000 0.000 4418.071 7482.650 0.000 5172.728
## 345 346 347 348 349 350 351 352
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 353 354 355 356 357 358 359 360
## 6432.744 5976.170 0.000 4121.160 0.000 0.000 0.000 0.000
## 361 362 363 364 365 366 367 368
## 5285.394 0.000 0.000 5054.093 0.000 0.000 0.000 0.000
## 369 370 371 372 373 374 375 376
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 5335.288
## 377 378 379 380 381 382 383 384
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 385 386 387 388 389 390 391 392
## 0.000 0.000 0.000 0.000 0.000 4248.370 0.000 0.000
## 393 394 395 396 397 398 399 400
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4906.214
## 401 402 403 404 405 406 407 408
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 409 410 411 412 413 414 415 416
## 0.000 0.000 0.000 4733.234 0.000 0.000 4750.170 0.000
## 417 418 419 420 421 422 423 424
## 0.000 0.000 0.000 0.000 4957.193 6953.478 6649.642 0.000
## 425 426 427 428 429 430 431 432
## 0.000 0.000 0.000 0.000 5232.060 0.000 0.000 0.000
## 433 434 435 436 437 438 439 440
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 441 442 443 444 445 446 447 448
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 449 450 451 452 453 454 455 456
## 5891.145 5936.302 0.000 0.000 0.000 0.000 0.000 6248.901
## 457 458 459 460 461 462 463 464
## 0.000 7460.280 0.000 0.000 0.000 0.000 0.000 0.000
## 465 466 467 468 469 470 471 472
## 0.000 0.000 6808.783 4239.256 0.000 0.000 0.000 5350.144
## 473 474 475 476 477 478 479 480
## 0.000 0.000 0.000 0.000 7031.717 4821.085 0.000 0.000
## 481 482 483 484 485 486 487 488
## 0.000 0.000 0.000 0.000 5054.732 5156.531 0.000 0.000
## 489 490 491 492 493 494 495 496
## 0.000 6490.070 5404.977 0.000 0.000 0.000 0.000 4636.621
## 497 498 499 500 501 502 503 504
## 0.000 0.000 0.000 0.000 0.000 0.000 4606.546 0.000
## 505 506 507 508 509 510 511 512
## 6904.102 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 513 514 515 516 517 518 519 520
## 0.000 0.000 0.000 0.000 7244.168 0.000 0.000 7255.120
## 521 522 523 524 525 526 527 528
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 529 530 531 532 533 534 535 536
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 537 538 539 540 541 542 543 544
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 545 546 547 548 549 550 551 552
## 0.000 0.000 0.000 7315.510 0.000 0.000 0.000 0.000
## 553 554 555 556 557 558 559 560
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 561 562 563 564 565 566 567 568
## 0.000 0.000 0.000 0.000 4547.021 0.000 6108.173 0.000
## 569 570 571 572 573 574 575 576
## 0.000 4685.575 0.000 0.000 0.000 0.000 0.000 0.000
## 577 578 579 580 581 582 583 584
## 0.000 0.000 0.000 0.000 0.000 5819.177 0.000 4281.428
## 585 586 587 588 589 590 591 592
## 0.000 0.000 0.000 0.000 5695.009 0.000 0.000 0.000
## 593 594 595 596 597 598 599 600
## 0.000 0.000 4882.506 4492.539 NA 0.000 0.000 3608.387
## 601 602 603 604 605 606 607 608
## 5516.032 0.000 0.000 0.000 0.000 0.000 7217.174 0.000
## 609 610 611 612 613 614 615 616
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 617 618 619 620 621 622 623 624
## 0.000 0.000 0.000 7257.339 0.000 0.000 0.000 0.000
## 625 626 627 628 629 630 631 632
## 0.000 8393.521 6160.348 0.000 0.000 5325.100 0.000 0.000
## 633 634 635 636 637 638 639 640
## 0.000 0.000 0.000 0.000 0.000 6169.289 0.000 0.000
## 641 642 643 644 645 646 647 648
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 649 650 651 652 653 654 655 656
## 0.000 0.000 0.000 0.000 5215.720 0.000 0.000 0.000
## 657 658 659 660 661 662 663 664
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 665 666 667 668 669 670 671 672
## 0.000 5572.143 0.000 0.000 0.000 0.000 0.000 4174.040
## 673 674 675 676 677 678 679 680
## 5705.315 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 681 682 683 684 685 686 687 688
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 689 690 691 692 693 694 695 696
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 697 698 699 700 701 702 703 704
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 705 706 707 708 709 710 711 712
## 0.000 0.000 0.000 5893.608 0.000 0.000 0.000 0.000
## 713 714 715 716 717 718 719 720
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 721 722 723 724 725 726 727 728
## 5262.107 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 729 730 731 732 733 734 735 736
## 0.000 0.000 3915.067 6729.606 0.000 0.000 0.000 0.000
## 737 738 739 740 741 742 743 744
## 0.000 0.000 0.000 0.000 4859.104 0.000 4632.958 0.000
## 745 746 747 748 749 750 751 752
## 0.000 0.000 6333.132 0.000 0.000 0.000 0.000 0.000
## 753 754 755 756 757 758 759 760
## 4624.901 NA 0.000 0.000 0.000 0.000 0.000 0.000
## 761 762 763 764 765 766 767 768
## 0.000 5573.808 0.000 7411.161 4879.736 5319.826 0.000 0.000
## 769 770 771 772 773 774 775 776
## 0.000 0.000 0.000 0.000 0.000 6251.188 0.000 0.000
## 777 778 779 780 781 782 783 784
## 0.000 0.000 0.000 0.000 0.000 6695.185 0.000 0.000
## 785 786 787 788 789 790 791 792
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 793 794 795 796 797 798 799 800
## 0.000 0.000 0.000 0.000 0.000 4641.350 6332.597 0.000
## 801 802 803 804 805 806 807 808
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 809 810 811 812 813 814 815 816
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 817 818 819 820 821 822 823 824
## 0.000 6913.294 6594.283 0.000 4777.920 0.000 0.000 4519.739
## 825 826 827 828 829 830 831 832
## 5693.148 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 833 834 835 836 837 838 839 840
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 841 842 843 844 845 846 847 848
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 849 850 851 852 853 854 855 856
## 6830.224 5524.305 6725.353 0.000 0.000 0.000 6186.450 0.000
## 857 858 859 860 861 862 863 864
## 0.000 0.000 5213.194 0.000 0.000 5458.911 0.000 0.000
## 865 866 867 868 869 870 871 872
## 0.000 0.000 5947.022 0.000 0.000 5664.951 0.000 7598.274
## 873 874 875 876 877 878 879 880
## 0.000 5590.781 3503.232 0.000 0.000 0.000 0.000 0.000
## 881 882 883 884 885 886 887 888
## 0.000 0.000 0.000 0.000 5295.700 0.000 6934.576 0.000
## 889 890 891 892 893 894 895 896
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 897 898 899 900 901 902 903 904
## 0.000 0.000 0.000 0.000 0.000 0.000 6346.439 0.000
## 905 906 907 908 909 910 911 912
## 0.000 0.000 NA 0.000 0.000 0.000 6837.345 0.000
## 913 914 915 916 917 918 919 920
## 0.000 0.000 0.000 0.000 7760.779 4775.519 0.000 0.000
## 921 922 923 924 925 926 927 928
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 929 930 931 932 933 934 935 936
## 5034.844 0.000 0.000 4856.103 0.000 0.000 0.000 0.000
## 937 938 939 940 941 942 943 944
## 0.000 0.000 0.000 0.000 5310.618 0.000 0.000 0.000
## 945 946 947 948 949 950 951 952
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 953 954 955 956 957 958 959 960
## 0.000 4843.225 0.000 0.000 0.000 0.000 0.000 0.000
## 961 962 963 964 965 966 967 968
## 0.000 0.000 0.000 0.000 0.000 6875.781 0.000 0.000
## 969 970 971 972 973 974 975 976
## 0.000 0.000 5309.937 0.000 0.000 0.000 0.000 0.000
## 977 978 979 980 981 982 983 984
## 0.000 0.000 0.000 0.000 0.000 0.000 5422.135 4999.322
## 985 986 987 988 989 990 991 992
## 5537.809 5727.931 0.000 0.000 0.000 6546.481 0.000 0.000
## 993 994 995 996 997 998 999 1000
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1001 1002 1003 1004 1005 1006 1007 1008
## 0.000 7289.280 6292.301 0.000 0.000 0.000 0.000 0.000
## 1009 1010 1011 1012 1013 1014 1015 1016
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1017 1018 1019 1020 1021 1022 1023 1024
## 0.000 0.000 0.000 0.000 0.000 0.000 7913.074 0.000
## 1025 1026 1027 1028 1029 1030 1031 1032
## 6506.584 4640.733 0.000 0.000 0.000 0.000 0.000 0.000
## 1033 1034 1035 1036 1037 1038 1039 1040
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1041 1042 1043 1044 1045 1046 1047 1048
## 0.000 0.000 3426.357 0.000 4214.611 0.000 0.000 0.000
## 1049 1050 1051 1052 1053 1054 1055 1056
## 0.000 0.000 5227.218 0.000 4948.486 0.000 0.000 0.000
## 1057 1058 1059 1060 1061 1062 1063 1064
## 0.000 0.000 4746.100 5385.210 0.000 4351.973 0.000 0.000
## 1065 1066 1067 1068 1069 1070 1071 1072
## 0.000 0.000 0.000 0.000 0.000 4176.099 0.000 0.000
## 1073 1074 1075 1076 1077 1078 1079 1080
## 0.000 6880.506 0.000 0.000 0.000 0.000 5607.576 0.000
## 1081 1082 1083 1084 1085 1086 1087 1088
## 6984.803 6709.498 0.000 0.000 4383.501 6868.757 0.000 0.000
## 1089 1090 1091 1092 1093 1094 1095 1096
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1097 1098 1099 1100 1101 1102 1103 1104
## 0.000 0.000 0.000 4205.585 0.000 0.000 0.000 0.000
## 1105 1106 1107 1108 1109 1110 1111 1112
## 0.000 0.000 0.000 0.000 0.000 0.000 5182.965 0.000
## 1113 1114 1115 1116 1117 1118 1119 1120
## 0.000 0.000 0.000 0.000 0.000 6709.209 6223.129 0.000
## 1121 1122 1123 1124 1125 1126 1127 1128
## 0.000 0.000 0.000 0.000 0.000 0.000 8912.265 0.000
## 1129 1130 1131 1132 1133 1134 1135 1136
## 0.000 0.000 0.000 0.000 5712.423 0.000 6310.516 0.000
## 1137 1138 1139 1140 1141 1142 1143 1144
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1145 1146 1147 1148 1149 1150 1151 1152
## 5463.160 0.000 0.000 7196.456 0.000 6822.587 0.000 5751.812
## 1153 1154 1155 1156 1157 1158 1159 1160
## 0.000 0.000 6275.183 0.000 0.000 0.000 0.000 0.000
## 1161 1162 1163 1164 1165 1166 1167 1168
## 0.000 0.000 0.000 0.000 0.000 5050.639 0.000 0.000
## 1169 1170 1171 1172 1173 1174 1175 1176
## 0.000 0.000 0.000 7041.006 6108.312 6815.829 0.000 0.000
## 1177 1178 1179 1180 1181 1182 1183 1184
## 0.000 0.000 0.000 5580.595 0.000 3747.483 0.000 0.000
## 1185 1186 1187 1188 1189 1190 1191 1192
## 3846.994 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1193 1194 1195 1196 1197 1198 1199 1200
## 0.000 5409.701 0.000 0.000 0.000 0.000 0.000 0.000
## 1201 1202 1203 1204 1205 1206 1207 1208
## 0.000 0.000 0.000 0.000 0.000 0.000 3536.531 0.000
## 1209 1210 1211 1212 1213 1214 1215 1216
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1217 1218 1219 1220 1221 1222 1223 1224
## 6260.202 0.000 0.000 0.000 0.000 0.000 6330.222 0.000
## 1225 1226 1227 1228 1229 1230 1231 1232
## 4989.314 0.000 0.000 0.000 0.000 6936.248 0.000 0.000
## 1233 1234 1235 1236 1237 1238 1239 1240
## 0.000 5751.840 0.000 0.000 0.000 6438.584 0.000 0.000
## 1241 1242 1243 1244 1245 1246 1247 1248
## 0.000 0.000 0.000 0.000 0.000 7192.531 0.000 0.000
## 1249 1250 1251 1252 1253 1254 1255 1256
## 0.000 0.000 0.000 4215.831 0.000 0.000 0.000 0.000
## 1257 1258 1259 1260 1261 1262 1263 1264
## NA 0.000 0.000 0.000 0.000 0.000 0.000 NA
## 1265 1266 1267 1268 1269 1270 1271 1272
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1273 1274 1275 1276 1277 1278 1279 1280
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1281 1282 1283 1284 1285 1286 1287 1288
## 5428.112 0.000 0.000 0.000 0.000 0.000 4561.558 0.000
## 1289 1290 1291 1292 1293 1294 1295 1296
## 0.000 0.000 6678.837 0.000 0.000 0.000 0.000 0.000
## 1297 1298 1299 1300 1301 1302 1303 1304
## 0.000 0.000 6126.466 0.000 0.000 0.000 0.000 0.000
## 1305 1306 1307 1308 1309 1310 1311 1312
## 0.000 0.000 0.000 0.000 0.000 5076.144 4901.860 0.000
## 1313 1314 1315 1316 1317 1318 1319 1320
## 6085.861 0.000 0.000 0.000 0.000 0.000 0.000 NA
## 1321 1322 1323 1324 1325 1326 1327 1328
## 0.000 0.000 4236.719 0.000 0.000 0.000 0.000 0.000
## 1329 1330 1331 1332 1333 1334 1335 1336
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1337 1338 1339 1340 1341 1342 1343 1344
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1345 1346 1347 1348 1349 1350 1351 1352
## NA 0.000 0.000 0.000 0.000 0.000 0.000 4719.092
## 1353 1354 1355 1356 1357 1358 1359 1360
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1361 1362 1363 1364 1365 1366 1367 1368
## 0.000 0.000 6768.419 0.000 0.000 0.000 6637.771 3595.377
## 1369 1370 1371 1372 1373 1374 1375 1376
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1377 1378 1379 1380 1381 1382 1383 1384
## 0.000 0.000 0.000 0.000 8113.193 6031.657 0.000 0.000
## 1385 1386 1387 1388 1389 1390 1391 1392
## 0.000 0.000 0.000 0.000 0.000 0.000 5366.899 0.000
## 1393 1394 1395 1396 1397 1398 1399 1400
## 0.000 0.000 0.000 0.000 0.000 6007.533 0.000 0.000
## 1401 1402 1403 1404 1405 1406 1407 1408
## 0.000 0.000 6504.564 4461.362 0.000 0.000 0.000 0.000
## 1409 1410 1411 1412 1413 1414 1415 1416
## 0.000 5960.671 0.000 0.000 0.000 0.000 0.000 0.000
## 1417 1418 1419 1420 1421 1422 1423 1424
## 0.000 0.000 0.000 0.000 0.000 6396.493 4785.100 0.000
## 1425 1426 1427 1428 1429 1430 1431 1432
## 0.000 6749.695 0.000 0.000 0.000 0.000 0.000 0.000
## 1433 1434 1435 1436 1437 1438 1439 1440
## 0.000 0.000 0.000 0.000 0.000 NA 0.000 0.000
## 1441 1442 1443 1444 1445 1446 1447 1448
## 0.000 5575.614 0.000 0.000 0.000 4881.547 NA 0.000
## 1449 1450 1451 1452 1453 1454 1455 1456
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1457 1458 1459 1460 1461 1462 1463 1464
## 5645.008 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1465 1466 1467 1468 1469 1470 1471 1472
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1473 1474 1475 1476 1477 1478 1479 1480
## 0.000 0.000 0.000 0.000 4335.014 0.000 0.000 0.000
## 1481 1482 1483 1484 1485 1486 1487 1488
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1489 1490 1491 1492 1493 1494 1495 1496
## 5904.515 0.000 0.000 4381.385 0.000 0.000 6229.020 0.000
## 1497 1498 1499 1500 1501 1502 1503 1504
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 5267.192
## 1505 1506 1507 1508 1509 1510 1511 1512
## 0.000 0.000 5095.101 0.000 0.000 0.000 0.000 0.000
## 1513 1514 1515 1516 1517 1518 1519 1520
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1521 1522 1523 1524 1525 1526 1527 1528
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1529 1530 1531 1532 1533 1534 1535 1536
## 0.000 4973.152 0.000 0.000 0.000 0.000 0.000 0.000
## 1537 1538 1539 1540 1541 1542 1543 1544
## 0.000 0.000 5667.814 6760.523 0.000 0.000 0.000 0.000
## 1545 1546 1547 1548 1549 1550 1551 1552
## 5847.446 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1553 1554 1555 1556 1557 1558 1559 1560
## 0.000 5612.621 0.000 0.000 0.000 0.000 0.000 0.000
## 1561 1562 1563 1564 1565 1566 1567 1568
## 0.000 0.000 0.000 0.000 7166.470 0.000 0.000 0.000
## 1569 1570 1571 1572 1573 1574 1575 1576
## 0.000 0.000 5361.613 0.000 0.000 0.000 0.000 0.000
## 1577 1578 1579 1580 1581 1582 1583 1584
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1585 1586 1587 1588 1589 1590 1591 1592
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 5996.193
## 1593 1594 1595 1596 1597 1598 1599 1600
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1601 1602 1603 1604 1605 1606 1607 1608
## 5559.496 0.000 0.000 NA 0.000 7158.428 0.000 0.000
## 1609 1610 1611 1612 1613 1614 1615 1616
## 0.000 4873.533 0.000 0.000 0.000 6861.509 0.000 5559.262
## 1617 1618 1619 1620 1621 1622 1623 1624
## 0.000 6030.426 0.000 0.000 5233.554 0.000 6012.400 0.000
## 1625 1626 1627 1628 1629 1630 1631 1632
## 0.000 0.000 0.000 0.000 0.000 6496.079 0.000 5244.937
## 1633 1634 1635 1636 1637 1638 1639 1640
## 0.000 0.000 0.000 0.000 6024.966 0.000 0.000 0.000
## 1641 1642 1643 1644 1645 1646 1647 1648
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1649 1650 1651 1652 1653 1654 1655 1656
## 0.000 4095.290 0.000 0.000 0.000 0.000 6675.684 0.000
## 1657 1658 1659 1660 1661 1662 1663 1664
## 0.000 0.000 0.000 0.000 5036.260 8356.651 4343.948 6755.248
## 1665 1666 1667 1668 1669 1670 1671 1672
## 6530.786 0.000 0.000 0.000 5371.681 0.000 5399.944 0.000
## 1673 1674 1675 1676 1677 1678 1679 1680
## 5815.950 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1681 1682 1683 1684 1685 1686 1687 1688
## 0.000 4690.875 5638.786 0.000 0.000 0.000 0.000 0.000
## 1689 1690 1691 1692 1693 1694 1695 1696
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4865.409
## 1697 1698 1699 1700 1701 1702 1703 1704
## 0.000 5594.100 4691.226 0.000 0.000 0.000 0.000 0.000
## 1705 1706 1707 1708 1709 1710 1711 1712
## 0.000 0.000 NA 0.000 5597.763 0.000 0.000 0.000
## 1713 1714 1715 1716 1717 1718 1719 1720
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1721 1722 1723 1724 1725 1726 1727 1728
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1729 1730 1731 1732 1733 1734 1735 1736
## 6366.190 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1737 1738 1739 1740 1741 1742 1743 1744
## 0.000 0.000 0.000 0.000 5031.367 0.000 0.000 0.000
## 1745 1746 1747 1748 1749 1750 1751 1752
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1753 1754 1755 1756 1757 1758 1759 1760
## 0.000 4389.859 0.000 0.000 0.000 0.000 0.000 0.000
## 1761 1762 1763 1764 1765 1766 1767 1768
## 7176.761 0.000 0.000 0.000 0.000 4861.931 0.000 0.000
## 1769 1770 1771 1772 1773 1774 1775 1776
## 0.000 0.000 0.000 0.000 0.000 6824.111 0.000 0.000
## 1777 1778 1779 1780 1781 1782 1783 1784
## 4780.055 0.000 5018.836 0.000 0.000 0.000 0.000 0.000
## 1785 1786 1787 1788 1789 1790 1791 1792
## 0.000 0.000 0.000 0.000 4245.770 0.000 0.000 0.000
## 1793 1794 1795 1796 1797 1798 1799 1800
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1801 1802 1803 1804 1805 1806 1807 1808
## 0.000 0.000 0.000 0.000 0.000 0.000 5174.165 5898.036
## 1809 1810 1811 1812 1813 1814 1815 1816
## 0.000 0.000 0.000 0.000 5179.408 0.000 0.000 0.000
## 1817 1818 1819 1820 1821 1822 1823 1824
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1825 1826 1827 1828 1829 1830 1831 1832
## 0.000 4929.268 0.000 0.000 0.000 0.000 0.000 0.000
## 1833 1834 1835 1836 1837 1838 1839 1840
## 0.000 0.000 0.000 0.000 0.000 NA 0.000 5445.802
## 1841 1842 1843 1844 1845 1846 1847 1848
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1849 1850 1851 1852 1853 1854 1855 1856
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1857 1858 1859 1860 1861 1862 1863 1864
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1865 1866 1867 1868 1869 1870 1871 1872
## 0.000 0.000 0.000 0.000 0.000 0.000 5887.182 0.000
## 1873 1874 1875 1876 1877 1878 1879 1880
## 0.000 0.000 0.000 0.000 0.000 6065.051 0.000 0.000
## 1881 1882 1883 1884 1885 1886 1887 1888
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1889 1890 1891 1892 1893 1894 1895 1896
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1897 1898 1899 1900 1901 1902 1903 1904
## 0.000 0.000 0.000 4204.661 0.000 0.000 0.000 0.000
## 1905 1906 1907 1908 1909 1910 1911 1912
## 0.000 0.000 0.000 0.000 0.000 6242.812 0.000 0.000
## 1913 1914 1915 1916 1917 1918 1919 1920
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1921 1922 1923 1924 1925 1926 1927 1928
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1929 1930 1931 1932 1933 1934 1935 1936
## 0.000 0.000 0.000 0.000 0.000 7316.304 0.000 0.000
## 1937 1938 1939 1940 1941 1942 1943 1944
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1945 1946 1947 1948 1949 1950 1951 1952
## 0.000 0.000 0.000 0.000 3300.204 0.000 0.000 0.000
## 1953 1954 1955 1956 1957 1958 1959 1960
## 4791.363 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1961 1962 1963 1964 1965 1966 1967 1968
## 6600.605 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1969 1970 1971 1972 1973 1974 1975 1976
## 0.000 0.000 0.000 0.000 0.000 5401.739 0.000 0.000
## 1977 1978 1979 1980 1981 1982 1983 1984
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 1985 1986 1987 1988 1989 1990 1991 1992
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4550.490
## 1993 1994 1995 1996 1997 1998 1999 2000
## 6877.573 6313.547 0.000 0.000 0.000 6923.021 0.000 0.000
## 2001 2002 2003 2004 2005 2006 2007 2008
## 5930.305 0.000 5287.196 0.000 5844.087 0.000 0.000 0.000
## 2009 2010 2011 2012 2013 2014 2015 2016
## 0.000 0.000 0.000 0.000 5019.293 0.000 0.000 0.000
## 2017 2018 2019 2020 2021 2022 2023 2024
## 0.000 4321.072 7004.309 0.000 0.000 0.000 0.000 0.000
## 2025 2026 2027 2028 2029 2030 2031 2032
## 0.000 0.000 0.000 0.000 0.000 4178.214 0.000 0.000
## 2033 2034 2035 2036 2037 2038 2039 2040
## 0.000 0.000 5710.700 0.000 0.000 0.000 5420.453 0.000
## 2041 2042 2043 2044 2045 2046 2047 2048
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 5376.570
## 2049 2050 2051 2052 2053 2054 2055 2056
## 0.000 0.000 0.000 0.000 0.000 0.000 5637.280 0.000
## 2057 2058 2059 2060 2061 2062 2063 2064
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 2065 2066 2067 2068 2069 2070 2071 2072
## 0.000 0.000 0.000 4543.979 0.000 0.000 0.000 0.000
## 2073 2074 2075 2076 2077 2078 2079 2080
## 7807.939 0.000 0.000 0.000 6143.344 0.000 0.000 5672.914
## 2081 2082 2083 2084 2085 2086 2087 2088
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 2089 2090 2091 2092 2093 2094 2095 2096
## 0.000 4799.944 0.000 0.000 0.000 0.000 0.000 4751.927
## 2097 2098 2099 2100 2101 2102 2103 2104
## 0.000 0.000 8334.052 4442.980 NA 0.000 5388.466 0.000
## 2105 2106 2107 2108 2109 2110 2111 2112
## 0.000 0.000 4656.371 0.000 0.000 0.000 5244.470 0.000
## 2113 2114 2115 2116 2117 2118 2119 2120
## 0.000 0.000 0.000 0.000 5813.373 0.000 4787.678 0.000
## 2121 2122 2123 2124 2125 2126 2127 2128
## 0.000 0.000 6373.741 0.000 0.000 0.000 0.000 0.000
## 2129 2130 2131 2132 2133 2134 2135 2136
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 2137 2138 2139 2140 2141
## 0.000 0.000 0.000 0.000 0.000