library(blorr)
library(ggplot2)
library(magrittr)
Model
model <- glm(y ~ ., data = bank_marketing, family = binomial(link = 'logit'))
Forward Selection
Selection Summary
blr_step_aic_forward(model)
#> Forward Selection Method
#> ------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#>
#> Variables Entered:
#>
#> - duration
#> - poutcome
#> - month
#> - contact
#> - housing
#> - loan
#> - campaign
#> - marital
#> - education
#> - age
#>
#> No more variables to be added.
#>
#> Selection Summary
#> -----------------------------------------------------
#> Step Variable AIC BIC Deviance
#> -----------------------------------------------------
#> 1 duration 2674.384 2687.217 2670.384
#> 2 poutcome 2396.014 2396.014 2396.014
#> 3 month 2274.109 2274.109 2274.109
#> 4 contact 2207.884 2207.884 2207.884
#> 5 housing 2184.550 2184.550 2184.550
#> 6 loan 2171.972 2171.972 2171.972
#> 7 campaign 2164.164 2164.164 2164.164
#> 8 marital 2158.524 2158.524 2158.524
#> 9 education 2155.837 2155.837 2155.837
#> 10 age 2154.272 2154.272 2154.272
#> -----------------------------------------------------
Detailed Output
blr_step_aic_forward(model, details = TRUE)
#> Forward Selection Method
#> ------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#> Step 0: AIC = 3216.659
#> y ~ 1
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> duration 1 2674.384 2687.217 2670.384
#> poutcome 1 2952.014 2977.680 2944.014
#> month 1 3068.991 3145.988 3044.991
#> contact 1 3096.276 3115.525 3090.276
#> housing 1 3146.378 3159.211 3142.378
#> job 1 3163.390 3240.388 3139.390
#> pdays 1 3179.547 3192.380 3175.547
#> campaign 1 3187.507 3200.340 3183.507
#> previous 1 3187.805 3200.638 3183.805
#> loan 1 3191.998 3204.830 3187.998
#> education 1 3197.612 3223.278 3189.612
#> marital 1 3198.977 3218.226 3192.977
#> balance 1 3200.456 3213.289 3196.456
#> default 1 3212.619 3225.452 3208.619
#> age 1 3213.913 3226.746 3209.913
#> day 1 3215.266 3228.099 3211.266
#> ---------------------------------------------------
#>
#>
#> - duration
#>
#>
#> Step 1 : AIC = 2674.384
#> y ~ duration
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> poutcome 1 2396.014 2428.097 2386.014
#> month 1 2501.687 2585.101 2475.687
#> contact 1 2538.800 2564.466 2530.800
#> housing 1 2598.905 2618.155 2592.905
#> job 1 2604.187 2687.601 2578.187
#> pdays 1 2625.686 2644.936 2619.686
#> previous 1 2632.723 2651.973 2626.723
#> campaign 1 2649.575 2668.824 2643.575
#> education 1 2649.712 2681.794 2639.712
#> loan 1 2650.927 2670.177 2644.927
#> marital 1 2655.816 2681.482 2647.816
#> balance 1 2665.192 2684.441 2659.192
#> age 1 2669.825 2689.075 2663.825
#> default 1 2671.465 2690.714 2665.465
#> day 1 2671.945 2691.194 2665.945
#> ---------------------------------------------------
#>
#> - poutcome
#>
#>
#> Step 2 : AIC = 2396.014
#> y ~ duration + poutcome
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> month 1 2274.109 2376.773 2242.109
#> contact 1 2315.977 2360.892 2301.977
#> housing 1 2330.897 2369.396 2318.897
#> job 1 2360.724 2463.387 2328.724
#> education 1 2374.980 2426.312 2358.980
#> loan 1 2379.044 2417.543 2367.044
#> marital 1 2381.743 2426.658 2367.743
#> campaign 1 2383.767 2422.266 2371.767
#> age 1 2394.129 2432.627 2382.129
#> balance 1 2394.670 2433.169 2382.670
#> default 1 2395.142 2433.641 2383.142
#> pdays 1 2395.489 2433.988 2383.489
#> day 1 2395.768 2434.267 2383.768
#> previous 1 2397.323 2435.822 2385.323
#> ---------------------------------------------------
#>
#> - month
#>
#>
#> Step 3 : AIC = 2274.109
#> y ~ duration + poutcome + month
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> contact 1 2207.884 2323.381 2171.884
#> housing 1 2248.264 2357.344 2214.264
#> loan 1 2261.151 2370.231 2227.151
#> education 1 2262.659 2384.572 2224.659
#> marital 1 2262.944 2378.441 2226.944
#> campaign 1 2263.636 2372.717 2229.636
#> job 1 2268.492 2441.737 2214.492
#> default 1 2274.291 2383.371 2240.291
#> balance 1 2274.440 2383.520 2240.440
#> previous 1 2275.315 2384.396 2241.315
#> day 1 2275.696 2384.776 2241.696
#> pdays 1 2275.699 2384.779 2241.699
#> age 1 2276.044 2385.124 2242.044
#> ---------------------------------------------------
#>
#> - contact
#>
#>
#> Step 4 : AIC = 2207.884
#> y ~ duration + poutcome + month + contact
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> housing 1 2184.550 2306.463 2146.550
#> loan 1 2194.028 2315.941 2156.028
#> campaign 1 2199.390 2321.303 2161.390
#> marital 1 2200.044 2328.374 2160.044
#> education 1 2201.153 2335.900 2159.153
#> job 1 2206.818 2392.896 2148.818
#> default 1 2208.191 2330.105 2170.191
#> balance 1 2208.199 2330.113 2170.199
#> pdays 1 2208.994 2330.908 2170.994
#> previous 1 2209.022 2330.935 2171.022
#> age 1 2209.363 2331.277 2171.363
#> day 1 2209.717 2331.630 2171.717
#> ---------------------------------------------------
#>
#> - housing
#>
#>
#> Step 5 : AIC = 2184.55
#> y ~ duration + poutcome + month + contact + housing
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> loan 1 2171.972 2300.302 2131.972
#> campaign 1 2177.501 2305.831 2137.501
#> marital 1 2177.790 2312.537 2135.790
#> education 1 2178.893 2320.055 2134.893
#> default 1 2184.500 2312.830 2144.500
#> previous 1 2185.704 2314.034 2145.704
#> balance 1 2185.723 2314.053 2145.723
#> pdays 1 2186.347 2314.677 2146.347
#> day 1 2186.533 2314.863 2146.533
#> age 1 2186.538 2314.868 2146.538
#> job 1 2187.688 2380.183 2127.688
#> ---------------------------------------------------
#>
#> - loan
#>
#>
#> Step 6 : AIC = 2171.972
#> y ~ duration + poutcome + month + contact + housing + loan
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> campaign 1 2164.164 2298.910 2122.164
#> marital 1 2165.935 2307.098 2121.935
#> education 1 2167.741 2315.320 2121.741
#> default 1 2172.581 2307.328 2130.581
#> previous 1 2172.993 2307.739 2130.993
#> balance 1 2173.517 2308.263 2131.517
#> pdays 1 2173.705 2308.451 2131.705
#> day 1 2173.949 2308.695 2131.949
#> age 1 2173.949 2308.696 2131.949
#> job 1 2175.333 2374.244 2113.333
#> ---------------------------------------------------
#>
#> - campaign
#>
#>
#> Step 7 : AIC = 2164.164
#> y ~ duration + poutcome + month + contact + housing + loan + campaign
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> marital 1 2158.524 2306.103 2112.524
#> education 1 2159.748 2313.744 2111.748
#> default 1 2164.942 2306.105 2120.942
#> previous 1 2165.522 2306.685 2121.522
#> balance 1 2165.643 2306.806 2121.643
#> pdays 1 2165.931 2307.094 2121.931
#> day 1 2165.994 2307.156 2121.994
#> age 1 2166.153 2307.316 2122.153
#> job 1 2168.292 2373.619 2104.292
#> ---------------------------------------------------
#>
#> - marital
#>
#>
#> Step 8 : AIC = 2158.524
#> y ~ duration + poutcome + month + contact + housing + loan + campaign + marital
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> education 1 2155.837 2322.666 2103.837
#> age 1 2157.894 2311.890 2109.894
#> default 1 2159.199 2313.195 2111.199
#> balance 1 2159.872 2313.868 2111.872
#> previous 1 2159.890 2313.885 2111.890
#> day 1 2160.324 2314.320 2112.324
#> pdays 1 2160.358 2314.353 2112.358
#> job 1 2161.946 2380.107 2093.946
#> ---------------------------------------------------
#>
#> - education
#>
#>
#> Step 9 : AIC = 2155.837
#> y ~ duration + poutcome + month + contact + housing + loan + campaign + marital + education
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> age 1 2154.272 2327.517 2100.272
#> default 1 2156.625 2329.870 2102.625
#> previous 1 2157.299 2330.544 2103.299
#> balance 1 2157.538 2330.783 2103.538
#> day 1 2157.550 2330.795 2103.550
#> pdays 1 2157.730 2330.976 2103.730
#> job 1 2159.754 2397.164 2085.754
#> ---------------------------------------------------
#>
#> - age
#>
#>
#> Step 10 : AIC = 2154.272
#> y ~ duration + poutcome + month + contact + housing + loan + campaign + marital + education + age
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> default 1 2155.132 2334.794 2099.132
#> previous 1 2155.627 2335.289 2099.627
#> day 1 2155.942 2335.603 2099.942
#> balance 1 2156.105 2335.767 2100.105
#> pdays 1 2156.185 2335.847 2100.185
#> job 1 2160.639 2404.465 2084.639
#> ---------------------------------------------------
#>
#>
#> No more variables to be added.
#>
#> Variables Entered:
#>
#> - duration
#> - poutcome
#> - month
#> - contact
#> - housing
#> - loan
#> - campaign
#> - marital
#> - education
#> - age
#>
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4494 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.4500 0.4220 -15.2834 0.0000
#> duration 1 0.0043 2e-04 20.6728 0.0000
#> poutcomefailure 1 -0.0607 0.1848 -0.3286 0.7424
#> poutcomeother 1 0.4960 0.2501 1.9829 0.0474
#> poutcomesuccess 1 2.8061 0.2193 12.7976 0.0000
#> monthjun 1 0.9457 0.2497 3.7878 2e-04
#> monthjul 1 -0.1077 0.2248 -0.4791 0.6319
#> monthaug 1 -0.2323 0.2353 -0.9871 0.3236
#> monthoct 1 1.5139 0.3301 4.5867 0.0000
#> monthnov 1 -0.2024 0.2428 -0.8336 0.4045
#> monthdec 1 1.1022 0.7666 1.4377 0.1505
#> monthjan 1 -0.6857 0.3538 -1.9383 0.0526
#> monthfeb 1 0.3908 0.2481 1.5750 0.1152
#> monthmar 1 1.5948 0.3935 4.0524 1e-04
#> monthapr 1 0.2393 0.2366 1.0115 0.3118
#> monthsep 1 1.7156 0.3810 4.5032 0.0000
#> contactcellular 1 1.7353 0.2371 7.3195 0.0000
#> contacttelephone 1 1.3093 0.3235 4.0477 1e-04
#> housingno 1 0.5636 0.1364 4.1307 0.0000
#> loanno 1 0.6997 0.2043 3.4243 6e-04
#> campaign 1 -0.0861 0.0302 -2.8505 0.0044
#> maritalsingle 1 0.4474 0.1423 3.1449 0.0017
#> maritaldivorced 1 -0.1397 0.2051 -0.6809 0.4959
#> educationsecondary 1 -0.2693 0.1313 -2.0512 0.0402
#> educationunknown 1 0.2768 0.2802 0.9880 0.3232
#> educationprimary 1 -0.4408 0.1981 -2.2251 0.0261
#> age 1 0.0116 0.0061 1.8920 0.0585
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9082 Somers' D 0.8164
#> % Discordant 0.0918 Gamma 0.8164
#> % Tied 0.0000 Tau-a 0.1654
#> Pairs 2070068 c 0.9082
#> ---------------------------------------------------------------
#>
#> Selection Summary
#> -----------------------------------------------------
#> Step Variable AIC BIC Deviance
#> -----------------------------------------------------
#> 1 duration 2674.384 2687.217 2670.384
#> 2 poutcome 2396.014 2396.014 2396.014
#> 3 month 2274.109 2274.109 2274.109
#> 4 contact 2207.884 2207.884 2207.884
#> 5 housing 2184.550 2184.550 2184.550
#> 6 loan 2171.972 2171.972 2171.972
#> 7 campaign 2164.164 2164.164 2164.164
#> 8 marital 2158.524 2158.524 2158.524
#> 9 education 2155.837 2155.837 2155.837
#> 10 age 2154.272 2154.272 2154.272
#> -----------------------------------------------------
Plot
model %>%
blr_step_aic_forward() %>%
plot()
#> Forward Selection Method
#> ------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#>
#> Variables Entered:
#>
#> - duration
#> - poutcome
#> - month
#> - contact
#> - housing
#> - loan
#> - campaign
#> - marital
#> - education
#> - age
#>
#> No more variables to be added.
Backward Elimination
Selection Summary
blr_step_aic_backward(model)
#> Backward Elimination Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#>
#> Variables Removed:
#>
#> - job
#> - balance
#> - pdays
#> - day
#> - previous
#> - default
#>
#>
#> Backward Elimination Summary
#> ----------------------------------------------
#> Variable AIC BIC Deviance
#> ----------------------------------------------
#> Full Model 2168.379 2444.288 2082.379
#> job 2161.974 2367.301 2097.974
#> balance 2160.081 2358.992 2098.081
#> pdays 2158.198 2350.692 2098.198
#> day 2156.520 2342.598 2098.520
#> previous 2155.132 2334.794 2099.132
#> default 2154.272 2327.517 2100.272
#> ----------------------------------------------
Detailed Output
blr_step_aic_backward(model, details = TRUE)
#> Backward Elimination Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#> Step 0: AIC = 2168.379
#> y ~ age + job + marital + education + default + balance + housing + loan + contact + day + month + duration + campaign + pdays + previous + poutcome
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> job 1 2161.974 2367.301 2097.974
#> balance 1 2166.454 2435.946 2082.454
#> pdays 1 2166.524 2436.016 2082.524
#> day 1 2166.672 2436.164 2082.672
#> previous 1 2167.064 2436.556 2083.064
#> default 1 2167.404 2436.896 2083.404
#> age 1 2167.426 2436.918 2083.426
#> education 1 2170.473 2427.133 2090.473
#> marital 1 2174.410 2437.486 2092.410
#> campaign 1 2175.158 2444.651 2091.158
#> loan 1 2178.932 2448.425 2094.932
#> housing 1 2182.756 2452.249 2098.756
#> contact 1 2223.027 2486.103 2141.027
#> month 1 2225.989 2431.317 2161.989
#> poutcome 1 2315.414 2572.074 2235.414
#> duration 1 2750.857 3020.350 2666.857
#> ---------------------------------------------------
#>
#>
#> - job
#>
#>
#> Step 1 : AIC = 2161.974
#> y ~ age + marital + education + default + balance + housing + loan + contact + day + month + duration + campaign + pdays + previous + poutcome
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> balance 1 2160.081 2358.992 2098.081
#> pdays 1 2160.086 2358.997 2098.086
#> day 1 2160.271 2359.182 2098.271
#> previous 1 2160.619 2359.530 2098.619
#> default 1 2161.041 2359.952 2099.041
#> age 1 2163.482 2362.393 2101.482
#> education 1 2165.150 2351.228 2107.150
#> campaign 1 2169.477 2368.389 2107.477
#> marital 1 2169.513 2362.008 2109.513
#> loan 1 2172.155 2371.066 2110.155
#> housing 1 2176.398 2375.309 2114.398
#> contact 1 2218.720 2411.215 2158.720
#> month 1 2225.363 2360.110 2183.363
#> poutcome 1 2313.283 2499.361 2255.283
#> duration 1 2737.119 2936.030 2675.119
#> ---------------------------------------------------
#>
#> - balance
#>
#>
#> Step 2 : AIC = 2160.081
#> y ~ age + marital + education + default + housing + loan + contact + day + month + duration + campaign + pdays + previous + poutcome
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> pdays 1 2158.198 2350.692 2098.198
#> day 1 2158.392 2350.887 2098.392
#> previous 1 2158.733 2351.228 2098.733
#> default 1 2159.178 2351.672 2099.178
#> age 1 2161.701 2354.196 2101.701
#> education 1 2163.533 2343.195 2107.533
#> campaign 1 2167.570 2360.065 2107.570
#> marital 1 2167.622 2353.700 2109.622
#> loan 1 2170.407 2362.901 2110.407
#> housing 1 2174.712 2367.207 2114.712
#> contact 1 2216.841 2402.919 2158.841
#> month 1 2223.804 2352.133 2183.804
#> poutcome 1 2312.874 2492.535 2256.874
#> duration 1 2738.964 2931.458 2678.964
#> ---------------------------------------------------
#>
#> - pdays
#>
#>
#> Step 3 : AIC = 2158.198
#> y ~ age + marital + education + default + housing + loan + contact + day + month + duration + campaign + previous + poutcome
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> day 1 2156.520 2342.598 2098.520
#> previous 1 2156.801 2342.879 2098.801
#> default 1 2157.307 2343.385 2099.307
#> age 1 2159.837 2345.915 2101.837
#> education 1 2161.730 2334.975 2107.730
#> campaign 1 2165.740 2351.818 2107.740
#> marital 1 2165.804 2345.466 2109.804
#> loan 1 2168.467 2354.546 2110.467
#> housing 1 2173.210 2359.288 2115.210
#> contact 1 2214.841 2394.503 2158.841
#> month 1 2221.861 2343.775 2183.861
#> poutcome 1 2317.460 2490.705 2263.460
#> duration 1 2736.979 2923.057 2678.979
#> ---------------------------------------------------
#>
#> - day
#>
#>
#> Step 4 : AIC = 2156.52
#> y ~ age + marital + education + default + housing + loan + contact + month + duration + campaign + previous + poutcome
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> previous 1 2155.132 2334.794 2099.132
#> default 1 2155.627 2335.289 2099.627
#> age 1 2158.118 2337.780 2102.118
#> education 1 2159.940 2326.768 2107.940
#> campaign 1 2163.740 2343.402 2107.740
#> marital 1 2164.069 2337.314 2110.069
#> loan 1 2167.123 2346.784 2111.123
#> housing 1 2171.891 2351.553 2115.891
#> contact 1 2212.958 2386.203 2158.958
#> month 1 2221.559 2337.056 2185.559
#> poutcome 1 2316.222 2483.051 2264.222
#> duration 1 2734.987 2914.649 2678.987
#> ---------------------------------------------------
#>
#> - previous
#>
#>
#> Step 5 : AIC = 2155.132
#> y ~ age + marital + education + default + housing + loan + contact + month + duration + campaign + poutcome
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> default 1 2154.272 2327.517 2100.272
#> age 1 2156.625 2329.870 2102.625
#> education 1 2158.621 2319.034 2108.621
#> marital 1 2162.584 2329.413 2110.584
#> campaign 1 2162.680 2335.925 2108.680
#> loan 1 2165.637 2338.883 2111.637
#> housing 1 2170.521 2343.766 2116.521
#> contact 1 2211.460 2378.289 2159.460
#> month 1 2219.833 2328.914 2185.833
#> poutcome 1 2328.851 2489.263 2278.851
#> duration 1 2733.745 2906.990 2679.745
#> ---------------------------------------------------
#>
#> - default
#>
#>
#> Step 6 : AIC = 2154.272
#> y ~ age + marital + education + housing + loan + contact + month + duration + campaign + poutcome
#>
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> age 1 2155.837 2322.666 2103.837
#> education 1 2157.894 2311.890 2109.894
#> marital 1 2161.646 2322.059 2111.646
#> campaign 1 2161.983 2328.812 2109.983
#> loan 1 2165.333 2332.162 2113.333
#> housing 1 2169.510 2336.339 2117.510
#> contact 1 2210.770 2371.183 2160.770
#> month 1 2219.654 2322.318 2187.654
#> poutcome 1 2328.640 2482.636 2280.640
#> duration 1 2733.878 2900.707 2681.878
#> ---------------------------------------------------
#>
#> No more variables to be removed.
#>
#> Variables Removed:
#>
#> - job
#> - balance
#> - pdays
#> - day
#> - previous
#> - default
#>
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4494 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.4500 0.4220 -15.2834 0.0000
#> age 1 0.0116 0.0061 1.8920 0.0585
#> maritalsingle 1 0.4474 0.1423 3.1449 0.0017
#> maritaldivorced 1 -0.1397 0.2051 -0.6809 0.4959
#> educationsecondary 1 -0.2693 0.1313 -2.0512 0.0402
#> educationunknown 1 0.2768 0.2802 0.9880 0.3232
#> educationprimary 1 -0.4408 0.1981 -2.2251 0.0261
#> housingno 1 0.5636 0.1364 4.1307 0.0000
#> loanno 1 0.6997 0.2043 3.4243 6e-04
#> contactcellular 1 1.7353 0.2371 7.3195 0.0000
#> contacttelephone 1 1.3093 0.3235 4.0477 1e-04
#> monthjun 1 0.9457 0.2497 3.7878 2e-04
#> monthjul 1 -0.1077 0.2248 -0.4791 0.6319
#> monthaug 1 -0.2323 0.2353 -0.9871 0.3236
#> monthoct 1 1.5139 0.3301 4.5867 0.0000
#> monthnov 1 -0.2024 0.2428 -0.8336 0.4045
#> monthdec 1 1.1022 0.7666 1.4377 0.1505
#> monthjan 1 -0.6857 0.3538 -1.9383 0.0526
#> monthfeb 1 0.3908 0.2481 1.5750 0.1152
#> monthmar 1 1.5948 0.3935 4.0524 1e-04
#> monthapr 1 0.2393 0.2366 1.0115 0.3118
#> monthsep 1 1.7156 0.3810 4.5032 0.0000
#> duration 1 0.0043 2e-04 20.6728 0.0000
#> campaign 1 -0.0861 0.0302 -2.8505 0.0044
#> poutcomefailure 1 -0.0607 0.1848 -0.3286 0.7424
#> poutcomeother 1 0.4960 0.2501 1.9829 0.0474
#> poutcomesuccess 1 2.8061 0.2193 12.7976 0.0000
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9082 Somers' D 0.8164
#> % Discordant 0.0918 Gamma 0.8164
#> % Tied 0.0000 Tau-a 0.1654
#> Pairs 2070068 c 0.9082
#> ---------------------------------------------------------------
#>
#>
#> Backward Elimination Summary
#> ----------------------------------------------
#> Variable AIC BIC Deviance
#> ----------------------------------------------
#> Full Model 2168.379 2444.288 2082.379
#> job 2161.974 2367.301 2097.974
#> balance 2160.081 2358.992 2098.081
#> pdays 2158.198 2350.692 2098.198
#> day 2156.520 2342.598 2098.520
#> previous 2155.132 2334.794 2099.132
#> default 2154.272 2327.517 2100.272
#> ----------------------------------------------
Plot
model %>%
blr_step_aic_backward() %>%
plot()
#> Backward Elimination Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#>
#> Variables Removed:
#>
#> - job
#> - balance
#> - pdays
#> - day
#> - previous
#> - default
#> Warning: Removed 2 rows containing missing values (geom_path).
#> Warning: Removed 2 rows containing missing values (geom_point).
#> Warning: Removed 2 rows containing missing values (geom_text).
Stepwise Selection
Selection Summary
blr_step_aic_both(model)
#> Stepwise Selection Method
#> -------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#>
#> Variables Entered/Removed:
#>
#> - duration added
#> - poutcome added
#> - month added
#> - contact added
#> - housing added
#> - loan added
#> - campaign added
#> - marital added
#> - education added
#> - age added
#>
#> No more variables to be added or removed.
#>
#>
#> Stepwise Summary
#> ---------------------------------------------------------
#> Variable Method AIC BIC Deviance
#> ---------------------------------------------------------
#> duration addition 2674.384 2687.217 2670.384
#> poutcome addition 2396.014 2428.097 2386.014
#> month addition 2274.109 2376.773 2242.109
#> contact addition 2207.884 2323.381 2171.884
#> housing addition 2184.550 2306.463 2146.550
#> loan addition 2171.972 2300.302 2131.972
#> campaign addition 2164.164 2298.910 2122.164
#> marital addition 2158.524 2306.103 2112.524
#> education addition 2155.837 2322.666 2103.837
#> age addition 2154.272 2327.517 2100.272
#> ---------------------------------------------------------
Detailed Output
blr_step_aic_both(model, details = TRUE)
#> Stepwise Selection Method
#> -------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#> Step 0: AIC = 3216.659
#> y ~ 1
#>
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> duration 1 2674.384 2687.217 2670.384
#> poutcome 1 2952.014 2977.680 2944.014
#> month 1 3068.991 3145.988 3044.991
#> contact 1 3096.276 3115.525 3090.276
#> housing 1 3146.378 3159.211 3142.378
#> job 1 3163.390 3240.388 3139.390
#> pdays 1 3179.547 3192.380 3175.547
#> campaign 1 3187.507 3200.340 3183.507
#> previous 1 3187.805 3200.638 3183.805
#> loan 1 3191.998 3204.830 3187.998
#> education 1 3197.612 3223.278 3189.612
#> marital 1 3198.977 3218.226 3192.977
#> balance 1 3200.456 3213.289 3196.456
#> default 1 3212.619 3225.452 3208.619
#> age 1 3213.913 3226.746 3209.913
#> day 1 3215.266 3228.099 3211.266
#> ---------------------------------------------------
#>
#> - duration added
#>
#>
#> Step 1 : AIC = 2674.384
#> y ~ duration
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> poutcome 1 2396.014 2428.097 2386.014
#> month 1 2501.687 2585.101 2475.687
#> contact 1 2538.800 2564.466 2530.800
#> housing 1 2598.905 2618.155 2592.905
#> job 1 2604.187 2687.601 2578.187
#> pdays 1 2625.686 2644.936 2619.686
#> previous 1 2632.723 2651.973 2626.723
#> campaign 1 2649.575 2668.824 2643.575
#> education 1 2649.712 2681.794 2639.712
#> loan 1 2650.927 2670.177 2644.927
#> marital 1 2655.816 2681.482 2647.816
#> balance 1 2665.192 2684.441 2659.192
#> age 1 2669.825 2689.075 2663.825
#> default 1 2671.465 2690.714 2665.465
#> day 1 2671.945 2691.194 2665.945
#> ---------------------------------------------------
#>
#> - poutcome added
#>
#>
#> Step 2 : AIC = 2396.014
#> y ~ duration + poutcome
#>
#> Remove Existing Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> poutcome 1 2674.384 2687.217 2670.384
#> duration 1 2952.014 2977.680 2944.014
#> ---------------------------------------------------
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> month 1 2274.109 2376.773 2242.109
#> contact 1 2315.977 2360.892 2301.977
#> housing 1 2330.897 2369.396 2318.897
#> job 1 2360.724 2463.387 2328.724
#> education 1 2374.980 2426.312 2358.980
#> loan 1 2379.044 2417.543 2367.044
#> marital 1 2381.743 2426.658 2367.743
#> campaign 1 2383.767 2422.266 2371.767
#> age 1 2394.129 2432.627 2382.129
#> balance 1 2394.670 2433.169 2382.670
#> default 1 2395.142 2433.641 2383.142
#> pdays 1 2395.489 2433.988 2383.489
#> day 1 2395.768 2434.267 2383.768
#> previous 1 2397.323 2435.822 2385.323
#> ---------------------------------------------------
#>
#> - month added
#>
#>
#> Step 3 : AIC = 2274.109
#> y ~ duration + poutcome + month
#>
#> Remove Existing Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> month 1 2396.014 2428.097 2386.014
#> poutcome 1 2501.687 2585.101 2475.687
#> duration 1 2849.726 2945.973 2819.726
#> ---------------------------------------------------
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> contact 1 2207.884 2323.381 2171.884
#> housing 1 2248.264 2357.344 2214.264
#> loan 1 2261.151 2370.231 2227.151
#> education 1 2262.659 2384.572 2224.659
#> marital 1 2262.944 2378.441 2226.944
#> campaign 1 2263.636 2372.717 2229.636
#> job 1 2268.492 2441.737 2214.492
#> default 1 2274.291 2383.371 2240.291
#> balance 1 2274.440 2383.520 2240.440
#> previous 1 2275.315 2384.396 2241.315
#> day 1 2275.696 2384.776 2241.696
#> pdays 1 2275.699 2384.779 2241.699
#> age 1 2276.044 2385.124 2242.044
#> ---------------------------------------------------
#>
#> - contact added
#>
#>
#> Step 4 : AIC = 2207.884
#> y ~ duration + poutcome + month + contact
#>
#> Remove Existing Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> contact 1 2274.109 2376.773 2242.109
#> month 1 2315.977 2360.892 2301.977
#> poutcome 1 2398.847 2495.094 2368.847
#> duration 1 2791.323 2900.403 2757.323
#> ---------------------------------------------------
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> housing 1 2184.550 2306.463 2146.550
#> loan 1 2194.028 2315.941 2156.028
#> campaign 1 2199.390 2321.303 2161.390
#> marital 1 2200.044 2328.374 2160.044
#> education 1 2201.153 2335.900 2159.153
#> job 1 2206.818 2392.896 2148.818
#> default 1 2208.191 2330.105 2170.191
#> balance 1 2208.199 2330.113 2170.199
#> pdays 1 2208.994 2330.908 2170.994
#> previous 1 2209.022 2330.935 2171.022
#> age 1 2209.363 2331.277 2171.363
#> day 1 2209.717 2331.630 2171.717
#> ---------------------------------------------------
#>
#> - housing added
#>
#>
#> Step 5 : AIC = 2184.55
#> y ~ duration + poutcome + month + contact + housing
#>
#> Remove Existing Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> housing 1 2207.884 2323.381 2171.884
#> contact 1 2248.264 2357.344 2214.264
#> month 1 2272.371 2323.703 2256.371
#> poutcome 1 2368.613 2471.277 2336.613
#> duration 1 2764.395 2879.892 2728.395
#> ---------------------------------------------------
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> loan 1 2171.972 2300.302 2131.972
#> campaign 1 2177.501 2305.831 2137.501
#> marital 1 2177.790 2312.537 2135.790
#> education 1 2178.893 2320.055 2134.893
#> default 1 2184.500 2312.830 2144.500
#> previous 1 2185.704 2314.034 2145.704
#> balance 1 2185.723 2314.053 2145.723
#> pdays 1 2186.347 2314.677 2146.347
#> day 1 2186.533 2314.863 2146.533
#> age 1 2186.538 2314.868 2146.538
#> job 1 2187.688 2380.183 2127.688
#> ---------------------------------------------------
#>
#> - loan added
#>
#>
#> Step 6 : AIC = 2171.972
#> y ~ duration + poutcome + month + contact + housing + loan
#>
#> Remove Existing Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> loan 1 2184.550 2306.463 2146.550
#> housing 1 2194.028 2315.941 2156.028
#> contact 1 2236.449 2351.946 2200.449
#> month 1 2254.571 2312.320 2236.571
#> poutcome 1 2352.384 2461.464 2318.384
#> duration 1 2749.734 2871.647 2711.734
#> ---------------------------------------------------
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> campaign 1 2164.164 2298.910 2122.164
#> marital 1 2165.935 2307.098 2121.935
#> education 1 2167.741 2315.320 2121.741
#> default 1 2172.581 2307.328 2130.581
#> previous 1 2172.993 2307.739 2130.993
#> balance 1 2173.517 2308.263 2131.517
#> pdays 1 2173.705 2308.451 2131.705
#> day 1 2173.949 2308.695 2131.949
#> age 1 2173.949 2308.696 2131.949
#> job 1 2175.333 2374.244 2113.333
#> ---------------------------------------------------
#>
#> - campaign added
#>
#>
#> Step 7 : AIC = 2164.164
#> y ~ duration + poutcome + month + contact + housing + loan + campaign
#>
#> Remove Existing Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> campaign 1 2171.972 2300.302 2131.972
#> loan 1 2177.501 2305.831 2137.501
#> housing 1 2184.780 2313.109 2144.780
#> contact 1 2226.786 2348.699 2188.786
#> month 1 2240.156 2304.321 2220.156
#> poutcome 1 2339.886 2455.383 2303.886
#> duration 1 2739.030 2867.360 2699.030
#> ---------------------------------------------------
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> marital 1 2158.524 2306.103 2112.524
#> education 1 2159.748 2313.744 2111.748
#> default 1 2164.942 2306.105 2120.942
#> previous 1 2165.522 2306.685 2121.522
#> balance 1 2165.643 2306.806 2121.643
#> pdays 1 2165.931 2307.094 2121.931
#> day 1 2165.994 2307.156 2121.994
#> age 1 2166.153 2307.316 2122.153
#> job 1 2168.292 2373.619 2104.292
#> ---------------------------------------------------
#>
#> - marital added
#>
#>
#> Step 8 : AIC = 2158.524
#> y ~ duration + poutcome + month + contact + housing + loan + campaign + marital
#>
#> Remove Existing Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> marital 1 2164.164 2298.910 2122.164
#> campaign 1 2165.935 2307.098 2121.935
#> loan 1 2171.156 2312.319 2127.156
#> housing 1 2178.493 2319.655 2134.493
#> contact 1 2217.559 2352.305 2175.559
#> month 1 2231.188 2308.185 2207.188
#> poutcome 1 2333.422 2461.752 2293.422
#> duration 1 2734.162 2875.325 2690.162
#> ---------------------------------------------------
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> education 1 2155.837 2322.666 2103.837
#> age 1 2157.894 2311.890 2109.894
#> default 1 2159.199 2313.195 2111.199
#> balance 1 2159.872 2313.868 2111.872
#> previous 1 2159.890 2313.885 2111.890
#> day 1 2160.324 2314.320 2112.324
#> pdays 1 2160.358 2314.353 2112.358
#> job 1 2161.946 2380.107 2093.946
#> ---------------------------------------------------
#>
#> - education added
#>
#>
#> Step 9 : AIC = 2155.837
#> y ~ duration + poutcome + month + contact + housing + loan + campaign + marital + education
#>
#> Remove Existing Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> education 1 2158.524 2306.103 2112.524
#> marital 1 2159.748 2313.744 2111.748
#> campaign 1 2163.512 2323.925 2113.512
#> loan 1 2167.139 2327.552 2117.139
#> housing 1 2174.888 2335.301 2124.888
#> contact 1 2211.259 2365.255 2163.259
#> month 1 2225.317 2321.564 2195.317
#> poutcome 1 2331.650 2479.229 2285.650
#> duration 1 2735.698 2896.111 2685.698
#> ---------------------------------------------------
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> age 1 2154.272 2327.517 2100.272
#> default 1 2156.625 2329.870 2102.625
#> previous 1 2157.299 2330.544 2103.299
#> balance 1 2157.538 2330.783 2103.538
#> day 1 2157.550 2330.795 2103.550
#> pdays 1 2157.730 2330.976 2103.730
#> job 1 2159.754 2397.164 2085.754
#> ---------------------------------------------------
#>
#> - age added
#>
#>
#> Step 10 : AIC = 2154.272
#> y ~ duration + poutcome + month + contact + housing + loan + campaign + marital + education + age
#>
#> Remove Existing Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> age 1 2155.837 2322.666 2103.837
#> education 1 2157.894 2311.890 2109.894
#> marital 1 2161.646 2322.059 2111.646
#> campaign 1 2161.983 2328.812 2109.983
#> loan 1 2165.333 2332.162 2113.333
#> housing 1 2169.510 2336.339 2117.510
#> contact 1 2210.770 2371.183 2160.770
#> month 1 2219.654 2322.318 2187.654
#> poutcome 1 2328.640 2482.636 2280.640
#> duration 1 2733.878 2900.707 2681.878
#> ---------------------------------------------------
#>
#> Enter New Variables
#> ---------------------------------------------------
#> Variable DF AIC BIC Deviance
#> ---------------------------------------------------
#> default 1 2155.132 2334.794 2099.132
#> previous 1 2155.627 2335.289 2099.627
#> day 1 2155.942 2335.603 2099.942
#> balance 1 2156.105 2335.767 2100.105
#> pdays 1 2156.185 2335.847 2100.185
#> job 1 2160.639 2404.465 2084.639
#> ---------------------------------------------------
#>
#>
#> No more variables to be added or removed.
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4494 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.4500 0.4220 -15.2834 0.0000
#> duration 1 0.0043 2e-04 20.6728 0.0000
#> poutcomefailure 1 -0.0607 0.1848 -0.3286 0.7424
#> poutcomeother 1 0.4960 0.2501 1.9829 0.0474
#> poutcomesuccess 1 2.8061 0.2193 12.7976 0.0000
#> monthjun 1 0.9457 0.2497 3.7878 2e-04
#> monthjul 1 -0.1077 0.2248 -0.4791 0.6319
#> monthaug 1 -0.2323 0.2353 -0.9871 0.3236
#> monthoct 1 1.5139 0.3301 4.5867 0.0000
#> monthnov 1 -0.2024 0.2428 -0.8336 0.4045
#> monthdec 1 1.1022 0.7666 1.4377 0.1505
#> monthjan 1 -0.6857 0.3538 -1.9383 0.0526
#> monthfeb 1 0.3908 0.2481 1.5750 0.1152
#> monthmar 1 1.5948 0.3935 4.0524 1e-04
#> monthapr 1 0.2393 0.2366 1.0115 0.3118
#> monthsep 1 1.7156 0.3810 4.5032 0.0000
#> contactcellular 1 1.7353 0.2371 7.3195 0.0000
#> contacttelephone 1 1.3093 0.3235 4.0477 1e-04
#> housingno 1 0.5636 0.1364 4.1307 0.0000
#> loanno 1 0.6997 0.2043 3.4243 6e-04
#> campaign 1 -0.0861 0.0302 -2.8505 0.0044
#> maritalsingle 1 0.4474 0.1423 3.1449 0.0017
#> maritaldivorced 1 -0.1397 0.2051 -0.6809 0.4959
#> educationsecondary 1 -0.2693 0.1313 -2.0512 0.0402
#> educationunknown 1 0.2768 0.2802 0.9880 0.3232
#> educationprimary 1 -0.4408 0.1981 -2.2251 0.0261
#> age 1 0.0116 0.0061 1.8920 0.0585
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9082 Somers' D 0.8164
#> % Discordant 0.0918 Gamma 0.8164
#> % Tied 0.0000 Tau-a 0.1654
#> Pairs 2070068 c 0.9082
#> ---------------------------------------------------------------
#>
#>
#> Stepwise Summary
#> ---------------------------------------------------------
#> Variable Method AIC BIC Deviance
#> ---------------------------------------------------------
#> duration addition 2674.384 2687.217 2670.384
#> poutcome addition 2396.014 2428.097 2386.014
#> month addition 2274.109 2376.773 2242.109
#> contact addition 2207.884 2323.381 2171.884
#> housing addition 2184.550 2306.463 2146.550
#> loan addition 2171.972 2300.302 2131.972
#> campaign addition 2164.164 2298.910 2122.164
#> marital addition 2158.524 2306.103 2112.524
#> education addition 2155.837 2322.666 2103.837
#> age addition 2154.272 2327.517 2100.272
#> ---------------------------------------------------------
Plot
model %>%
blr_step_aic_both() %>%
plot()
#> Stepwise Selection Method
#> -------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#>
#> Variables Entered/Removed:
#>
#> - duration added
#> - poutcome added
#> - month added
#> - contact added
#> - housing added
#> - loan added
#> - campaign added
#> - marital added
#> - education added
#> - age added
#>
#> No more variables to be added or removed.
Forward Selection
Selection Summary
blr_step_p_forward(model)
#> Forward Selection Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1. age
#> 2. job
#> 3. marital
#> 4. education
#> 5. default
#> 6. balance
#> 7. housing
#> 8. loan
#> 9. contact
#> 10. day
#> 11. month
#> 12. duration
#> 13. campaign
#> 14. pdays
#> 15. previous
#> 16. poutcome
#>
#> We are selecting variables based on p value...
#>
#> Variables Entered:
#>
#> - duration
#> - poutcome
#> - month
#> - contact
#> - housing
#> - loan
#> - campaign
#> - marital
#> - education
#> - age
#> - job
#>
#> No more variables to be added.
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4483 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3088 0.4552 -13.8591 0.0000
#> duration 1 0.0044 2e-04 20.7131 0.0000
#> poutcomefailure 1 -0.0708 0.1860 -0.3809 0.7033
#> poutcomeother 1 0.4931 0.2521 1.9561 0.0505
#> poutcomesuccess 1 2.7862 0.2214 12.5835 0.0000
#> monthjun 1 0.9644 0.2495 3.8661 1e-04
#> monthjul 1 -0.1080 0.2272 -0.4755 0.6345
#> monthaug 1 -0.2155 0.2382 -0.9049 0.3655
#> monthoct 1 1.5213 0.3346 4.5473 0.0000
#> monthnov 1 -0.1685 0.2448 -0.6885 0.4911
#> monthdec 1 0.9700 0.7726 1.2554 0.2093
#> monthjan 1 -0.6734 0.3596 -1.8725 0.0611
#> monthfeb 1 0.4067 0.2502 1.6255 0.1040
#> monthmar 1 1.5203 0.3950 3.8491 1e-04
#> monthapr 1 0.2207 0.2381 0.9268 0.3540
#> monthsep 1 1.6772 0.3913 4.2866 0.0000
#> contactcellular 1 1.7099 0.2369 7.2180 0.0000
#> contacttelephone 1 1.3259 0.3260 4.0673 0.0000
#> housingno 1 0.5747 0.1403 4.0970 0.0000
#> loanno 1 0.7109 0.2056 3.4575 5e-04
#> campaign 1 -0.0834 0.0304 -2.7471 0.0060
#> maritalsingle 1 0.4132 0.1443 2.8640 0.0042
#> maritaldivorced 1 -0.1610 0.2071 -0.7773 0.4370
#> educationsecondary 1 -0.3523 0.1711 -2.0585 0.0395
#> educationunknown 1 0.2947 0.3033 0.9718 0.3312
#> educationprimary 1 -0.4138 0.2434 -1.7001 0.0891
#> age 1 0.0076 0.0072 1.0578 0.2901
#> jobtechnician 1 0.0043 0.2075 0.0205 0.9836
#> jobentrepreneur 1 -0.3788 0.3822 -0.9910 0.3217
#> jobblue-collar 1 -0.0891 0.2413 -0.3694 0.7118
#> jobunknown 1 -0.9253 0.9525 -0.9714 0.3314
#> jobretired 1 0.4578 0.3111 1.4716 0.1411
#> jobadmin. 1 0.4029 0.2406 1.6745 0.0940
#> jobservices 1 0.2532 0.2681 0.9447 0.3448
#> jobself-employed 1 -0.0347 0.3126 -0.1110 0.9116
#> jobunemployed 1 -0.3796 0.3800 -0.9991 0.3178
#> jobhousemaid 1 -0.5142 0.4290 -1.1985 0.2307
#> jobstudent 1 0.0576 0.3785 0.1522 0.8790
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8200
#> % Discordant 0.0900 Gamma 0.8200
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
#>
#> Selection Summary
#> --------------------------------------------------------
#> Variable
#> Step Entered AIC BIC Deviance
#> --------------------------------------------------------
#> 1 duration 2674.3838 2687.2168 2670.3838
#> 2 poutcome 2396.0143 2428.0968 2386.0143
#> 3 month 2274.1092 2376.7730 2242.1092
#> 4 contact 2207.8841 2323.3809 2171.8841
#> 5 housing 2184.5501 2306.4634 2146.5501
#> 6 loan 2171.9722 2300.3020 2131.9722
#> 7 campaign 2164.1639 2298.9102 2122.1639
#> 8 marital 2158.5237 2306.1029 2112.5237
#> 9 education 2155.8369 2322.6656 2103.8369
#> 10 age 2154.2718 2327.5170 2100.2718
#> 11 job 2160.6387 2404.4652 2084.6387
#> --------------------------------------------------------
Detailed Output
blr_step_p_forward(model, details = TRUE)
#> Forward Selection Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1. age
#> 2. job
#> 3. marital
#> 4. education
#> 5. default
#> 6. balance
#> 7. housing
#> 8. loan
#> 9. contact
#> 10. day
#> 11. month
#> 12. duration
#> 13. campaign
#> 14. pdays
#> 15. previous
#> 16. poutcome
#>
#> We are selecting variables based on p value...
#>
#>
#> Forward Selection: Step 1
#>
#> - duration
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4519 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> ------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> ------------------------------------------------------------------
#> (Intercept) 1 -3.2978 0.0858 -38.4526 0.0000
#> duration 1 0.0037 2e-04 20.8847 0.0000
#> ------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.8181 Somers' D 0.6379
#> % Discordant 0.1809 Gamma 0.6372
#> % Tied 0.0010 Tau-a 0.1291
#> Pairs 2070068 c 0.8186
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 2
#>
#> - poutcome
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4516 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> ----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> ----------------------------------------------------------------------
#> (Intercept) 1 -3.7304 0.1036 -36.0223 0.0000
#> duration 1 0.0039 2e-04 20.8282 0.0000
#> poutcomefailure 1 0.4597 0.1662 2.7658 0.0057
#> poutcomeother 1 0.9144 0.2289 3.9955 1e-04
#> poutcomesuccess 1 3.3439 0.2027 16.4967 0.0000
#> ----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.8606 Somers' D 0.7219
#> % Discordant 0.1390 Gamma 0.7216
#> % Tied 5e-04 Tau-a 0.1462
#> Pairs 2070068 c 0.8608
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 3
#>
#> - month
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4505 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> ----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> ----------------------------------------------------------------------
#> (Intercept) 1 -4.4977 0.1634 -27.5205 0.0000
#> duration 1 0.0041 2e-04 20.9764 0.0000
#> poutcomefailure 1 0.2289 0.1802 1.2704 0.2039
#> poutcomeother 1 0.7266 0.2434 2.9851 0.0028
#> poutcomesuccess 1 3.1614 0.2114 14.9534 0.0000
#> monthjun 1 0.7262 0.2107 3.4457 6e-04
#> monthjul 1 0.6399 0.1998 3.2024 0.0014
#> monthaug 1 0.8630 0.1996 4.3238 0.0000
#> monthoct 1 2.5665 0.3144 8.1627 0.0000
#> monthnov 1 0.6606 0.2256 2.9278 0.0034
#> monthdec 1 2.1451 0.7506 2.8578 0.0043
#> monthjan 1 0.3876 0.3335 1.1621 0.2452
#> monthfeb 1 1.3033 0.2288 5.6964 0.0000
#> monthmar 1 2.7631 0.3727 7.4144 0.0000
#> monthapr 1 0.9654 0.2273 4.2480 0.0000
#> monthsep 1 2.7023 0.3513 7.6917 0.0000
#> ----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.8935 Somers' D 0.7870
#> % Discordant 0.1065 Gamma 0.7870
#> % Tied 0.0000 Tau-a 0.1594
#> Pairs 2070068 c 0.8935
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 4
#>
#> - contact
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4503 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -5.5654 0.2425 -22.9480 0.0000
#> duration 1 0.0042 2e-04 20.9910 0.0000
#> poutcomefailure 1 -0.1050 0.1823 -0.5759 0.5647
#> poutcomeother 1 0.3955 0.2444 1.6182 0.1056
#> poutcomesuccess 1 2.8860 0.2146 13.4492 0.0000
#> monthjun 1 1.3006 0.2362 5.5070 0.0000
#> monthjul 1 -0.1192 0.2160 -0.5521 0.5809
#> monthaug 1 0.1103 0.2128 0.5184 0.6042
#> monthoct 1 2.0192 0.3187 6.3356 0.0000
#> monthnov 1 -0.0239 0.2344 -0.1018 0.9189
#> monthdec 1 1.5531 0.7546 2.0582 0.0396
#> monthjan 1 -0.2942 0.3389 -0.8681 0.3853
#> monthfeb 1 0.6446 0.2367 2.7233 0.0065
#> monthmar 1 2.0912 0.3783 5.5285 0.0000
#> monthapr 1 0.3072 0.2340 1.3125 0.1893
#> monthsep 1 2.2170 0.3625 6.1152 0.0000
#> contactcellular 1 1.8567 0.2338 7.9423 0.0000
#> contacttelephone 1 1.5399 0.3153 4.8844 0.0000
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9016 Somers' D 0.8032
#> % Discordant 0.0984 Gamma 0.8032
#> % Tied 0.0000 Tau-a 0.1627
#> Pairs 2070068 c 0.9016
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 5
#>
#> - housing
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4502 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -5.6760 0.2452 -23.1446 0.0000
#> duration 1 0.0043 2e-04 20.8730 0.0000
#> poutcomefailure 1 -0.0518 0.1838 -0.2816 0.7783
#> poutcomeother 1 0.4490 0.2475 1.8144 0.0696
#> poutcomesuccess 1 2.8664 0.2168 13.2208 0.0000
#> monthjun 1 0.9695 0.2463 3.9363 1e-04
#> monthjul 1 -0.3280 0.2211 -1.4838 0.1379
#> monthaug 1 -0.3194 0.2303 -1.3871 0.1654
#> monthoct 1 1.6413 0.3263 5.0305 0.0000
#> monthnov 1 -0.2138 0.2408 -0.8881 0.3745
#> monthdec 1 1.1017 0.7773 1.4174 0.1564
#> monthjan 1 -0.6787 0.3519 -1.9287 0.0538
#> monthfeb 1 0.3840 0.2450 1.5675 0.1170
#> monthmar 1 1.7452 0.3884 4.4938 0.0000
#> monthapr 1 0.2601 0.2353 1.1054 0.2690
#> monthsep 1 1.8475 0.3744 4.9345 0.0000
#> contactcellular 1 1.8156 0.2342 7.7534 0.0000
#> contacttelephone 1 1.4055 0.3171 4.4318 0.0000
#> housingno 1 0.6643 0.1331 4.9895 0.0000
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9068 Somers' D 0.8137
#> % Discordant 0.0931 Gamma 0.8137
#> % Tied 0.0000 Tau-a 0.1649
#> Pairs 2070068 c 0.9069
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 6
#>
#> - loan
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4501 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -6.3293 0.3120 -20.2832 0.0000
#> duration 1 0.0042 2e-04 20.7811 0.0000
#> poutcomefailure 1 -0.0535 0.1841 -0.2906 0.7714
#> poutcomeother 1 0.4863 0.2484 1.9577 0.0503
#> poutcomesuccess 1 2.8391 0.2176 13.0491 0.0000
#> monthjun 1 0.9747 0.2469 3.9479 1e-04
#> monthjul 1 -0.2046 0.2232 -0.9168 0.3592
#> monthaug 1 -0.3488 0.2307 -1.5119 0.1306
#> monthoct 1 1.6098 0.3267 4.9271 0.0000
#> monthnov 1 -0.1809 0.2409 -0.7510 0.4526
#> monthdec 1 1.1086 0.7861 1.4103 0.1585
#> monthjan 1 -0.6682 0.3538 -1.8884 0.0590
#> monthfeb 1 0.4145 0.2453 1.6893 0.0912
#> monthmar 1 1.7041 0.3899 4.3708 0.0000
#> monthapr 1 0.2712 0.2357 1.1503 0.2500
#> monthsep 1 1.8237 0.3755 4.8568 0.0000
#> contactcellular 1 1.8250 0.2349 7.7696 0.0000
#> contacttelephone 1 1.3811 0.3181 4.3415 0.0000
#> housingno 1 0.6489 0.1334 4.8659 0.0000
#> loanno 1 0.7245 0.2010 3.6036 3e-04
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9078 Somers' D 0.8156
#> % Discordant 0.0922 Gamma 0.8156
#> % Tied 0.0000 Tau-a 0.1652
#> Pairs 2070068 c 0.9078
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 7
#>
#> - campaign
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4500 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -6.1334 0.3178 -19.2999 0.0000
#> duration 1 0.0043 2e-04 20.6910 0.0000
#> poutcomefailure 1 -0.0755 0.1836 -0.4112 0.6809
#> poutcomeother 1 0.4827 0.2486 1.9418 0.0522
#> poutcomesuccess 1 2.7964 0.2178 12.8371 0.0000
#> monthjun 1 0.9922 0.2470 4.0167 1e-04
#> monthjul 1 -0.1316 0.2241 -0.5873 0.5570
#> monthaug 1 -0.2420 0.2332 -1.0378 0.2994
#> monthoct 1 1.5741 0.3278 4.8022 0.0000
#> monthnov 1 -0.1844 0.2402 -0.7674 0.4429
#> monthdec 1 1.0838 0.7741 1.4000 0.1615
#> monthjan 1 -0.7119 0.3547 -2.0072 0.0447
#> monthfeb 1 0.4247 0.2457 1.7286 0.0839
#> monthmar 1 1.6952 0.3912 4.3332 0.0000
#> monthapr 1 0.2480 0.2358 1.0518 0.2929
#> monthsep 1 1.8103 0.3753 4.8239 0.0000
#> contactcellular 1 1.7993 0.2341 7.6856 0.0000
#> contacttelephone 1 1.4005 0.3181 4.4020 0.0000
#> housingno 1 0.6303 0.1335 4.7206 0.0000
#> loanno 1 0.7440 0.2015 3.6913 2e-04
#> campaign 1 -0.0872 0.0305 -2.8597 0.0042
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9078 Somers' D 0.8157
#> % Discordant 0.0922 Gamma 0.8157
#> % Tied 0.0000 Tau-a 0.1653
#> Pairs 2070068 c 0.9078
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 8
#>
#> - marital
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4498 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -6.2166 0.3232 -19.2362 0.0000
#> duration 1 0.0043 2e-04 20.6977 0.0000
#> poutcomefailure 1 -0.0618 0.1840 -0.3358 0.7370
#> poutcomeother 1 0.4844 0.2484 1.9502 0.0512
#> poutcomesuccess 1 2.7988 0.2186 12.8055 0.0000
#> monthjun 1 1.0072 0.2480 4.0613 0.0000
#> monthjul 1 -0.1173 0.2242 -0.5233 0.6008
#> monthaug 1 -0.1957 0.2343 -0.8353 0.4036
#> monthoct 1 1.5696 0.3278 4.7882 0.0000
#> monthnov 1 -0.1667 0.2413 -0.6909 0.4896
#> monthdec 1 1.1235 0.7726 1.4541 0.1459
#> monthjan 1 -0.6885 0.3536 -1.9472 0.0515
#> monthfeb 1 0.4190 0.2461 1.7027 0.0886
#> monthmar 1 1.6821 0.3913 4.2987 0.0000
#> monthapr 1 0.2403 0.2364 1.0167 0.3093
#> monthsep 1 1.7938 0.3768 4.7608 0.0000
#> contactcellular 1 1.7598 0.2347 7.4973 0.0000
#> contacttelephone 1 1.4023 0.3183 4.4051 0.0000
#> housingno 1 0.6240 0.1341 4.6540 0.0000
#> loanno 1 0.7328 0.2029 3.6122 3e-04
#> campaign 1 -0.0848 0.0303 -2.8016 0.0051
#> maritalsingle 1 0.3566 0.1256 2.8387 0.0045
#> maritaldivorced 1 -0.1138 0.2031 -0.5603 0.5753
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9074 Somers' D 0.8148
#> % Discordant 0.0926 Gamma 0.8148
#> % Tied 0.0000 Tau-a 0.1651
#> Pairs 2070068 c 0.9074
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 9
#>
#> - education
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4495 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -5.9983 0.3447 -17.4009 0.0000
#> duration 1 0.0043 2e-04 20.6767 0.0000
#> poutcomefailure 1 -0.0483 0.1844 -0.2619 0.7934
#> poutcomeother 1 0.5010 0.2493 2.0096 0.0445
#> poutcomesuccess 1 2.8168 0.2190 12.8614 0.0000
#> monthjun 1 0.9698 0.2485 3.9021 1e-04
#> monthjul 1 -0.1035 0.2247 -0.4606 0.6451
#> monthaug 1 -0.2130 0.2348 -0.9069 0.3645
#> monthoct 1 1.5774 0.3282 4.8063 0.0000
#> monthnov 1 -0.1724 0.2420 -0.7123 0.4763
#> monthdec 1 1.1275 0.7682 1.4677 0.1422
#> monthjan 1 -0.6652 0.3520 -1.8901 0.0587
#> monthfeb 1 0.4108 0.2475 1.6598 0.0970
#> monthmar 1 1.6334 0.3911 4.1765 0.0000
#> monthapr 1 0.2538 0.2365 1.0730 0.2833
#> monthsep 1 1.7658 0.3796 4.6515 0.0000
#> contactcellular 1 1.7250 0.2365 7.2926 0.0000
#> contacttelephone 1 1.3868 0.3196 4.3396 0.0000
#> housingno 1 0.6103 0.1339 4.5565 0.0000
#> loanno 1 0.7056 0.2043 3.4536 6e-04
#> campaign 1 -0.0858 0.0302 -2.8450 0.0044
#> maritalsingle 1 0.3269 0.1270 2.5736 0.0101
#> maritaldivorced 1 -0.1032 0.2032 -0.5081 0.6114
#> educationsecondary 1 -0.2625 0.1312 -2.0002 0.0455
#> educationunknown 1 0.3202 0.2793 1.1465 0.2516
#> educationprimary 1 -0.3637 0.1929 -1.8851 0.0594
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9075 Somers' D 0.8151
#> % Discordant 0.0924 Gamma 0.8151
#> % Tied 0.0000 Tau-a 0.1651
#> Pairs 2070068 c 0.9075
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 10
#>
#> - age
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4494 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.4500 0.4220 -15.2834 0.0000
#> duration 1 0.0043 2e-04 20.6728 0.0000
#> poutcomefailure 1 -0.0607 0.1848 -0.3286 0.7424
#> poutcomeother 1 0.4960 0.2501 1.9829 0.0474
#> poutcomesuccess 1 2.8061 0.2193 12.7976 0.0000
#> monthjun 1 0.9457 0.2497 3.7878 2e-04
#> monthjul 1 -0.1077 0.2248 -0.4791 0.6319
#> monthaug 1 -0.2323 0.2353 -0.9871 0.3236
#> monthoct 1 1.5139 0.3301 4.5867 0.0000
#> monthnov 1 -0.2024 0.2428 -0.8336 0.4045
#> monthdec 1 1.1022 0.7666 1.4377 0.1505
#> monthjan 1 -0.6857 0.3538 -1.9383 0.0526
#> monthfeb 1 0.3908 0.2481 1.5750 0.1152
#> monthmar 1 1.5948 0.3935 4.0524 1e-04
#> monthapr 1 0.2393 0.2366 1.0115 0.3118
#> monthsep 1 1.7156 0.3810 4.5032 0.0000
#> contactcellular 1 1.7353 0.2371 7.3195 0.0000
#> contacttelephone 1 1.3093 0.3235 4.0477 1e-04
#> housingno 1 0.5636 0.1364 4.1307 0.0000
#> loanno 1 0.6997 0.2043 3.4243 6e-04
#> campaign 1 -0.0861 0.0302 -2.8505 0.0044
#> maritalsingle 1 0.4474 0.1423 3.1449 0.0017
#> maritaldivorced 1 -0.1397 0.2051 -0.6809 0.4959
#> educationsecondary 1 -0.2693 0.1313 -2.0512 0.0402
#> educationunknown 1 0.2768 0.2802 0.9880 0.3232
#> educationprimary 1 -0.4408 0.1981 -2.2251 0.0261
#> age 1 0.0116 0.0061 1.8920 0.0585
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9082 Somers' D 0.8164
#> % Discordant 0.0918 Gamma 0.8164
#> % Tied 0.0000 Tau-a 0.1654
#> Pairs 2070068 c 0.9082
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Forward Selection: Step 11
#>
#> - job
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4483 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3088 0.4552 -13.8591 0.0000
#> duration 1 0.0044 2e-04 20.7131 0.0000
#> poutcomefailure 1 -0.0708 0.1860 -0.3809 0.7033
#> poutcomeother 1 0.4931 0.2521 1.9561 0.0505
#> poutcomesuccess 1 2.7862 0.2214 12.5835 0.0000
#> monthjun 1 0.9644 0.2495 3.8661 1e-04
#> monthjul 1 -0.1080 0.2272 -0.4755 0.6345
#> monthaug 1 -0.2155 0.2382 -0.9049 0.3655
#> monthoct 1 1.5213 0.3346 4.5473 0.0000
#> monthnov 1 -0.1685 0.2448 -0.6885 0.4911
#> monthdec 1 0.9700 0.7726 1.2554 0.2093
#> monthjan 1 -0.6734 0.3596 -1.8725 0.0611
#> monthfeb 1 0.4067 0.2502 1.6255 0.1040
#> monthmar 1 1.5203 0.3950 3.8491 1e-04
#> monthapr 1 0.2207 0.2381 0.9268 0.3540
#> monthsep 1 1.6772 0.3913 4.2866 0.0000
#> contactcellular 1 1.7099 0.2369 7.2180 0.0000
#> contacttelephone 1 1.3259 0.3260 4.0673 0.0000
#> housingno 1 0.5747 0.1403 4.0970 0.0000
#> loanno 1 0.7109 0.2056 3.4575 5e-04
#> campaign 1 -0.0834 0.0304 -2.7471 0.0060
#> maritalsingle 1 0.4132 0.1443 2.8640 0.0042
#> maritaldivorced 1 -0.1610 0.2071 -0.7773 0.4370
#> educationsecondary 1 -0.3523 0.1711 -2.0585 0.0395
#> educationunknown 1 0.2947 0.3033 0.9718 0.3312
#> educationprimary 1 -0.4138 0.2434 -1.7001 0.0891
#> age 1 0.0076 0.0072 1.0578 0.2901
#> jobtechnician 1 0.0043 0.2075 0.0205 0.9836
#> jobentrepreneur 1 -0.3788 0.3822 -0.9910 0.3217
#> jobblue-collar 1 -0.0891 0.2413 -0.3694 0.7118
#> jobunknown 1 -0.9253 0.9525 -0.9714 0.3314
#> jobretired 1 0.4578 0.3111 1.4716 0.1411
#> jobadmin. 1 0.4029 0.2406 1.6745 0.0940
#> jobservices 1 0.2532 0.2681 0.9447 0.3448
#> jobself-employed 1 -0.0347 0.3126 -0.1110 0.9116
#> jobunemployed 1 -0.3796 0.3800 -0.9991 0.3178
#> jobhousemaid 1 -0.5142 0.4290 -1.1985 0.2307
#> jobstudent 1 0.0576 0.3785 0.1522 0.8790
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8200
#> % Discordant 0.0900 Gamma 0.8200
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> No more variables to be added.
#>
#> Variables Entered:
#>
#> + duration
#> + poutcome
#> + month
#> + contact
#> + housing
#> + loan
#> + campaign
#> + marital
#> + education
#> + age
#> + job
#>
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4483 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3088 0.4552 -13.8591 0.0000
#> duration 1 0.0044 2e-04 20.7131 0.0000
#> poutcomefailure 1 -0.0708 0.1860 -0.3809 0.7033
#> poutcomeother 1 0.4931 0.2521 1.9561 0.0505
#> poutcomesuccess 1 2.7862 0.2214 12.5835 0.0000
#> monthjun 1 0.9644 0.2495 3.8661 1e-04
#> monthjul 1 -0.1080 0.2272 -0.4755 0.6345
#> monthaug 1 -0.2155 0.2382 -0.9049 0.3655
#> monthoct 1 1.5213 0.3346 4.5473 0.0000
#> monthnov 1 -0.1685 0.2448 -0.6885 0.4911
#> monthdec 1 0.9700 0.7726 1.2554 0.2093
#> monthjan 1 -0.6734 0.3596 -1.8725 0.0611
#> monthfeb 1 0.4067 0.2502 1.6255 0.1040
#> monthmar 1 1.5203 0.3950 3.8491 1e-04
#> monthapr 1 0.2207 0.2381 0.9268 0.3540
#> monthsep 1 1.6772 0.3913 4.2866 0.0000
#> contactcellular 1 1.7099 0.2369 7.2180 0.0000
#> contacttelephone 1 1.3259 0.3260 4.0673 0.0000
#> housingno 1 0.5747 0.1403 4.0970 0.0000
#> loanno 1 0.7109 0.2056 3.4575 5e-04
#> campaign 1 -0.0834 0.0304 -2.7471 0.0060
#> maritalsingle 1 0.4132 0.1443 2.8640 0.0042
#> maritaldivorced 1 -0.1610 0.2071 -0.7773 0.4370
#> educationsecondary 1 -0.3523 0.1711 -2.0585 0.0395
#> educationunknown 1 0.2947 0.3033 0.9718 0.3312
#> educationprimary 1 -0.4138 0.2434 -1.7001 0.0891
#> age 1 0.0076 0.0072 1.0578 0.2901
#> jobtechnician 1 0.0043 0.2075 0.0205 0.9836
#> jobentrepreneur 1 -0.3788 0.3822 -0.9910 0.3217
#> jobblue-collar 1 -0.0891 0.2413 -0.3694 0.7118
#> jobunknown 1 -0.9253 0.9525 -0.9714 0.3314
#> jobretired 1 0.4578 0.3111 1.4716 0.1411
#> jobadmin. 1 0.4029 0.2406 1.6745 0.0940
#> jobservices 1 0.2532 0.2681 0.9447 0.3448
#> jobself-employed 1 -0.0347 0.3126 -0.1110 0.9116
#> jobunemployed 1 -0.3796 0.3800 -0.9991 0.3178
#> jobhousemaid 1 -0.5142 0.4290 -1.1985 0.2307
#> jobstudent 1 0.0576 0.3785 0.1522 0.8790
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8200
#> % Discordant 0.0900 Gamma 0.8200
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
#>
#> Selection Summary
#> --------------------------------------------------------
#> Variable
#> Step Entered AIC BIC Deviance
#> --------------------------------------------------------
#> 1 duration 2674.3838 2687.2168 2670.3838
#> 2 poutcome 2396.0143 2428.0968 2386.0143
#> 3 month 2274.1092 2376.7730 2242.1092
#> 4 contact 2207.8841 2323.3809 2171.8841
#> 5 housing 2184.5501 2306.4634 2146.5501
#> 6 loan 2171.9722 2300.3020 2131.9722
#> 7 campaign 2164.1639 2298.9102 2122.1639
#> 8 marital 2158.5237 2306.1029 2112.5237
#> 9 education 2155.8369 2322.6656 2103.8369
#> 10 age 2154.2718 2327.5170 2100.2718
#> 11 job 2160.6387 2404.4652 2084.6387
#> --------------------------------------------------------
Plot
model %>%
blr_step_p_forward() %>%
plot()
#> Forward Selection Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1. age
#> 2. job
#> 3. marital
#> 4. education
#> 5. default
#> 6. balance
#> 7. housing
#> 8. loan
#> 9. contact
#> 10. day
#> 11. month
#> 12. duration
#> 13. campaign
#> 14. pdays
#> 15. previous
#> 16. poutcome
#>
#> We are selecting variables based on p value...
#>
#> Variables Entered:
#>
#> - duration
#> - poutcome
#> - month
#> - contact
#> - housing
#> - loan
#> - campaign
#> - marital
#> - education
#> - age
#> - job
#>
#> No more variables to be added.
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4483 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3088 0.4552 -13.8591 0.0000
#> duration 1 0.0044 2e-04 20.7131 0.0000
#> poutcomefailure 1 -0.0708 0.1860 -0.3809 0.7033
#> poutcomeother 1 0.4931 0.2521 1.9561 0.0505
#> poutcomesuccess 1 2.7862 0.2214 12.5835 0.0000
#> monthjun 1 0.9644 0.2495 3.8661 1e-04
#> monthjul 1 -0.1080 0.2272 -0.4755 0.6345
#> monthaug 1 -0.2155 0.2382 -0.9049 0.3655
#> monthoct 1 1.5213 0.3346 4.5473 0.0000
#> monthnov 1 -0.1685 0.2448 -0.6885 0.4911
#> monthdec 1 0.9700 0.7726 1.2554 0.2093
#> monthjan 1 -0.6734 0.3596 -1.8725 0.0611
#> monthfeb 1 0.4067 0.2502 1.6255 0.1040
#> monthmar 1 1.5203 0.3950 3.8491 1e-04
#> monthapr 1 0.2207 0.2381 0.9268 0.3540
#> monthsep 1 1.6772 0.3913 4.2866 0.0000
#> contactcellular 1 1.7099 0.2369 7.2180 0.0000
#> contacttelephone 1 1.3259 0.3260 4.0673 0.0000
#> housingno 1 0.5747 0.1403 4.0970 0.0000
#> loanno 1 0.7109 0.2056 3.4575 5e-04
#> campaign 1 -0.0834 0.0304 -2.7471 0.0060
#> maritalsingle 1 0.4132 0.1443 2.8640 0.0042
#> maritaldivorced 1 -0.1610 0.2071 -0.7773 0.4370
#> educationsecondary 1 -0.3523 0.1711 -2.0585 0.0395
#> educationunknown 1 0.2947 0.3033 0.9718 0.3312
#> educationprimary 1 -0.4138 0.2434 -1.7001 0.0891
#> age 1 0.0076 0.0072 1.0578 0.2901
#> jobtechnician 1 0.0043 0.2075 0.0205 0.9836
#> jobentrepreneur 1 -0.3788 0.3822 -0.9910 0.3217
#> jobblue-collar 1 -0.0891 0.2413 -0.3694 0.7118
#> jobunknown 1 -0.9253 0.9525 -0.9714 0.3314
#> jobretired 1 0.4578 0.3111 1.4716 0.1411
#> jobadmin. 1 0.4029 0.2406 1.6745 0.0940
#> jobservices 1 0.2532 0.2681 0.9447 0.3448
#> jobself-employed 1 -0.0347 0.3126 -0.1110 0.9116
#> jobunemployed 1 -0.3796 0.3800 -0.9991 0.3178
#> jobhousemaid 1 -0.5142 0.4290 -1.1985 0.2307
#> jobstudent 1 0.0576 0.3785 0.1522 0.8790
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8200
#> % Discordant 0.0900 Gamma 0.8200
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
Backward Elimination
Selection Summary
blr_step_p_backward(model)
#> Backward Elimination Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#> We are eliminating variables based on p value...
#>
#> Variables Removed:
#>
#> - balance
#> - pdays
#> - day
#> - previous
#> - default
#>
#> No more variables satisfy the condition of p value = 0.3
#>
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4483 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3088 0.4552 -13.8591 0.0000
#> age 1 0.0076 0.0072 1.0578 0.2901
#> jobtechnician 1 0.0043 0.2075 0.0205 0.9836
#> jobentrepreneur 1 -0.3788 0.3822 -0.9910 0.3217
#> jobblue-collar 1 -0.0891 0.2413 -0.3694 0.7118
#> jobunknown 1 -0.9253 0.9525 -0.9714 0.3314
#> jobretired 1 0.4578 0.3111 1.4716 0.1411
#> jobadmin. 1 0.4029 0.2406 1.6745 0.0940
#> jobservices 1 0.2532 0.2681 0.9447 0.3448
#> jobself-employed 1 -0.0347 0.3126 -0.1110 0.9116
#> jobunemployed 1 -0.3796 0.3800 -0.9991 0.3178
#> jobhousemaid 1 -0.5142 0.4290 -1.1985 0.2307
#> jobstudent 1 0.0576 0.3785 0.1522 0.8790
#> maritalsingle 1 0.4132 0.1443 2.8640 0.0042
#> maritaldivorced 1 -0.1610 0.2071 -0.7773 0.4370
#> educationsecondary 1 -0.3523 0.1711 -2.0585 0.0395
#> educationunknown 1 0.2947 0.3033 0.9718 0.3312
#> educationprimary 1 -0.4138 0.2434 -1.7001 0.0891
#> housingno 1 0.5747 0.1403 4.0970 0.0000
#> loanno 1 0.7109 0.2056 3.4575 5e-04
#> contactcellular 1 1.7099 0.2369 7.2180 0.0000
#> contacttelephone 1 1.3259 0.3260 4.0673 0.0000
#> monthjun 1 0.9644 0.2495 3.8661 1e-04
#> monthjul 1 -0.1080 0.2272 -0.4755 0.6345
#> monthaug 1 -0.2155 0.2382 -0.9049 0.3655
#> monthoct 1 1.5213 0.3346 4.5473 0.0000
#> monthnov 1 -0.1685 0.2448 -0.6885 0.4911
#> monthdec 1 0.9700 0.7726 1.2554 0.2093
#> monthjan 1 -0.6734 0.3596 -1.8725 0.0611
#> monthfeb 1 0.4067 0.2502 1.6255 0.1040
#> monthmar 1 1.5203 0.3950 3.8491 1e-04
#> monthapr 1 0.2207 0.2381 0.9268 0.3540
#> monthsep 1 1.6772 0.3913 4.2866 0.0000
#> duration 1 0.0044 2e-04 20.7131 0.0000
#> campaign 1 -0.0834 0.0304 -2.7471 0.0060
#> poutcomefailure 1 -0.0708 0.1860 -0.3809 0.7033
#> poutcomeother 1 0.4931 0.2521 1.9561 0.0505
#> poutcomesuccess 1 2.7862 0.2214 12.5835 0.0000
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8200
#> % Discordant 0.0900 Gamma 0.8200
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
#>
#>
#> Elimination Summary
#> -------------------------------------------------------
#> Variable
#> Step Removed AIC BIC Deviance
#> -------------------------------------------------------
#> 1 balance 2166.454 2435.947 2082.4539
#> 2 pdays 2164.602 2427.678 2082.6016
#> 3 day 2162.913 2419.573 2082.9134
#> 4 previous 2161.552 2411.795 2083.5518
#> 5 default 2160.639 2404.465 2084.6387
#> -------------------------------------------------------
Detailed Output
blr_step_p_backward(model, details = TRUE)
#> Backward Elimination Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#> We are eliminating variables based on p value...
#>
#> - balance
#>
#> Backward Elimination: Step 1
#>
#> Variable balance Removed
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4479 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3716 0.4726 -13.4832 0.0000
#> age 1 0.0076 0.0072 1.0491 0.2941
#> jobtechnician 1 9e-04 0.2082 0.0042 0.9967
#> jobentrepreneur 1 -0.3824 0.3825 -0.9998 0.3174
#> jobblue-collar 1 -0.0868 0.2417 -0.3589 0.7196
#> jobunknown 1 -0.9179 0.9546 -0.9616 0.3363
#> jobretired 1 0.4564 0.3117 1.4644 0.1431
#> jobadmin. 1 0.4093 0.2409 1.6989 0.0893
#> jobservices 1 0.2528 0.2684 0.9419 0.3463
#> jobself-employed 1 -0.0249 0.3136 -0.0794 0.9367
#> jobunemployed 1 -0.3872 0.3796 -1.0198 0.3078
#> jobhousemaid 1 -0.4960 0.4282 -1.1584 0.2467
#> jobstudent 1 0.0250 0.3804 0.0657 0.9476
#> maritalsingle 1 0.4203 0.1445 2.9091 0.0036
#> maritaldivorced 1 -0.1565 0.2071 -0.7556 0.4499
#> educationsecondary 1 -0.3448 0.1715 -2.0109 0.0443
#> educationunknown 1 0.3062 0.3043 1.0063 0.3143
#> educationprimary 1 -0.4081 0.2437 -1.6746 0.0940
#> defaultyes 1 -0.6471 0.6846 -0.9452 0.3445
#> housingno 1 0.5703 0.1409 4.0488 1e-04
#> loanno 1 0.6978 0.2065 3.3793 7e-04
#> contactcellular 1 1.7317 0.2393 7.2374 0.0000
#> contacttelephone 1 1.3527 0.3277 4.1280 0.0000
#> day 1 0.0046 0.0083 0.5510 0.5817
#> monthjun 1 0.9839 0.2528 3.8919 1e-04
#> monthjul 1 -0.1276 0.2308 -0.5528 0.5804
#> monthaug 1 -0.2286 0.2393 -0.9554 0.3394
#> monthoct 1 1.4855 0.3380 4.3947 0.0000
#> monthnov 1 -0.2033 0.2513 -0.8090 0.4185
#> monthdec 1 0.9870 0.7692 1.2832 0.1994
#> monthjan 1 -0.7564 0.3795 -1.9929 0.0463
#> monthfeb 1 0.4341 0.2567 1.6910 0.0908
#> monthmar 1 1.4993 0.3960 3.7861 2e-04
#> monthapr 1 0.1874 0.2413 0.7769 0.4372
#> monthsep 1 1.6614 0.3925 4.2327 0.0000
#> duration 1 0.0044 2e-04 20.7329 0.0000
#> campaign 1 -0.0838 0.0308 -2.7237 0.0065
#> pdays 1 -4e-04 0.0010 -0.3838 0.7011
#> previous 1 -0.0328 0.0403 -0.8148 0.4152
#> poutcomefailure 1 0.1079 0.3201 0.3370 0.7361
#> poutcomeother 1 0.6909 0.3679 1.8782 0.0603
#> poutcomesuccess 1 2.9570 0.3203 9.2323 0.0000
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8199
#> % Discordant 0.0900 Gamma 0.8199
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
#>
#>
#>
#> - pdays
#>
#> Backward Elimination: Step 2
#>
#> Variable pdays Removed
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4480 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3725 0.4726 -13.4848 0.0000
#> age 1 0.0076 0.0072 1.0488 0.2943
#> jobtechnician 1 -2e-04 0.2081 -0.0010 0.9992
#> jobentrepreneur 1 -0.3814 0.3824 -0.9974 0.3186
#> jobblue-collar 1 -0.0898 0.2416 -0.3716 0.7102
#> jobunknown 1 -0.9166 0.9527 -0.9621 0.3360
#> jobretired 1 0.4613 0.3113 1.4817 0.1384
#> jobadmin. 1 0.4071 0.2409 1.6899 0.0911
#> jobservices 1 0.2494 0.2684 0.9289 0.3529
#> jobself-employed 1 -0.0293 0.3135 -0.0936 0.9255
#> jobunemployed 1 -0.3853 0.3794 -1.0155 0.3099
#> jobhousemaid 1 -0.4899 0.4276 -1.1457 0.2519
#> jobstudent 1 0.0319 0.3799 0.0839 0.9331
#> maritalsingle 1 0.4208 0.1445 2.9129 0.0036
#> maritaldivorced 1 -0.1576 0.2071 -0.7608 0.4467
#> educationsecondary 1 -0.3464 0.1714 -2.0212 0.0433
#> educationunknown 1 0.3037 0.3042 0.9984 0.3181
#> educationprimary 1 -0.4109 0.2436 -1.6870 0.0916
#> defaultyes 1 -0.6502 0.6846 -0.9497 0.3422
#> housingno 1 0.5741 0.1405 4.0850 0.0000
#> loanno 1 0.6956 0.2064 3.3698 8e-04
#> contactcellular 1 1.7281 0.2392 7.2234 0.0000
#> contacttelephone 1 1.3482 0.3275 4.1167 0.0000
#> day 1 0.0047 0.0083 0.5585 0.5765
#> monthjun 1 0.9904 0.2525 3.9218 1e-04
#> monthjul 1 -0.1211 0.2302 -0.5260 0.5989
#> monthaug 1 -0.2202 0.2384 -0.9239 0.3555
#> monthoct 1 1.4926 0.3373 4.4250 0.0000
#> monthnov 1 -0.1883 0.2483 -0.7582 0.4483
#> monthdec 1 0.9844 0.7718 1.2754 0.2022
#> monthjan 1 -0.7475 0.3786 -1.9745 0.0483
#> monthfeb 1 0.4420 0.2560 1.7264 0.0843
#> monthmar 1 1.5032 0.3958 3.7979 1e-04
#> monthapr 1 0.1879 0.2412 0.7789 0.4360
#> monthsep 1 1.6694 0.3919 4.2599 0.0000
#> duration 1 0.0044 2e-04 20.7284 0.0000
#> campaign 1 -0.0840 0.0308 -2.7300 0.0063
#> previous 1 -0.0313 0.0401 -0.7808 0.4349
#> poutcomefailure 1 0.0160 0.2140 0.0748 0.9404
#> poutcomeother 1 0.6007 0.2839 2.1156 0.0344
#> poutcomesuccess 1 2.8839 0.2571 11.2151 0.0000
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8200
#> % Discordant 0.0900 Gamma 0.8200
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
#>
#>
#>
#> - day
#>
#> Backward Elimination: Step 3
#>
#> Variable day Removed
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4481 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3043 0.4562 -13.8180 0.0000
#> age 1 0.0075 0.0072 1.0444 0.2963
#> jobtechnician 1 0.0078 0.2076 0.0376 0.9700
#> jobentrepreneur 1 -0.3772 0.3826 -0.9859 0.3242
#> jobblue-collar 1 -0.0871 0.2416 -0.3604 0.7185
#> jobunknown 1 -0.9183 0.9530 -0.9635 0.3353
#> jobretired 1 0.4672 0.3110 1.5023 0.1330
#> jobadmin. 1 0.4062 0.2410 1.6853 0.0919
#> jobservices 1 0.2545 0.2683 0.9483 0.3430
#> jobself-employed 1 -0.0314 0.3132 -0.1002 0.9202
#> jobunemployed 1 -0.3800 0.3797 -1.0006 0.3170
#> jobhousemaid 1 -0.4949 0.4281 -1.1559 0.2477
#> jobstudent 1 0.0492 0.3785 0.1299 0.8967
#> maritalsingle 1 0.4180 0.1444 2.8947 0.0038
#> maritaldivorced 1 -0.1590 0.2071 -0.7676 0.4427
#> educationsecondary 1 -0.3489 0.1714 -2.0352 0.0418
#> educationunknown 1 0.2950 0.3037 0.9715 0.3313
#> educationprimary 1 -0.4105 0.2437 -1.6849 0.0920
#> defaultyes 1 -0.6503 0.6850 -0.9493 0.3425
#> housingno 1 0.5779 0.1404 4.1170 0.0000
#> loanno 1 0.7028 0.2062 3.4092 7e-04
#> contactcellular 1 1.7106 0.2370 7.2191 0.0000
#> contacttelephone 1 1.3309 0.3260 4.0831 0.0000
#> monthjun 1 0.9687 0.2495 3.8831 1e-04
#> monthjul 1 -0.1014 0.2273 -0.4460 0.6556
#> monthaug 1 -0.2174 0.2382 -0.9126 0.3614
#> monthoct 1 1.5162 0.3344 4.5340 0.0000
#> monthnov 1 -0.1659 0.2451 -0.6769 0.4985
#> monthdec 1 0.9675 0.7729 1.2517 0.2107
#> monthjan 1 -0.6822 0.3602 -1.8940 0.0582
#> monthfeb 1 0.4124 0.2502 1.6486 0.0992
#> monthmar 1 1.5169 0.3948 3.8417 1e-04
#> monthapr 1 0.2077 0.2384 0.8714 0.3835
#> monthsep 1 1.6648 0.3916 4.2518 0.0000
#> duration 1 0.0044 2e-04 20.7171 0.0000
#> campaign 1 -0.0812 0.0303 -2.6789 0.0074
#> previous 1 -0.0314 0.0401 -0.7834 0.4334
#> poutcomefailure 1 0.0130 0.2139 0.0608 0.9515
#> poutcomeother 1 0.5992 0.2839 2.1108 0.0348
#> poutcomesuccess 1 2.8822 0.2570 11.2167 0.0000
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9101 Somers' D 0.8201
#> % Discordant 0.0899 Gamma 0.8201
#> % Tied 0.0000 Tau-a 0.1662
#> Pairs 2070068 c 0.9101
#> ---------------------------------------------------------------
#>
#>
#>
#> - previous
#>
#> Backward Elimination: Step 4
#>
#> Variable previous Removed
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4482 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.2900 0.4556 -13.8046 0.0000
#> age 1 0.0074 0.0072 1.0330 0.3016
#> jobtechnician 1 0.0091 0.2076 0.0437 0.9652
#> jobentrepreneur 1 -0.3737 0.3828 -0.9764 0.3288
#> jobblue-collar 1 -0.0863 0.2417 -0.3569 0.7212
#> jobunknown 1 -0.9185 0.9529 -0.9639 0.3351
#> jobretired 1 0.4629 0.3112 1.4875 0.1369
#> jobadmin. 1 0.4066 0.2408 1.6884 0.0913
#> jobservices 1 0.2584 0.2683 0.9634 0.3354
#> jobself-employed 1 -0.0320 0.3129 -0.1021 0.9186
#> jobunemployed 1 -0.3797 0.3801 -0.9990 0.3178
#> jobhousemaid 1 -0.4974 0.4276 -1.1632 0.2447
#> jobstudent 1 0.0528 0.3784 0.1395 0.8891
#> maritalsingle 1 0.4165 0.1444 2.8843 0.0039
#> maritaldivorced 1 -0.1558 0.2069 -0.7531 0.4514
#> educationsecondary 1 -0.3520 0.1713 -2.0548 0.0399
#> educationunknown 1 0.2981 0.3033 0.9828 0.3257
#> educationprimary 1 -0.4083 0.2437 -1.6756 0.0938
#> defaultyes 1 -0.6574 0.6842 -0.9608 0.3366
#> housingno 1 0.5782 0.1404 4.1196 0.0000
#> loanno 1 0.7003 0.2060 3.3989 7e-04
#> contactcellular 1 1.7064 0.2367 7.2081 0.0000
#> contacttelephone 1 1.3177 0.3258 4.0441 1e-04
#> monthjun 1 0.9630 0.2493 3.8633 1e-04
#> monthjul 1 -0.1016 0.2274 -0.4466 0.6551
#> monthaug 1 -0.2126 0.2381 -0.8931 0.3718
#> monthoct 1 1.5166 0.3345 4.5342 0.0000
#> monthnov 1 -0.1617 0.2451 -0.6598 0.5094
#> monthdec 1 0.9666 0.7723 1.2516 0.2107
#> monthjan 1 -0.6776 0.3595 -1.8851 0.0594
#> monthfeb 1 0.4048 0.2502 1.6179 0.1057
#> monthmar 1 1.5149 0.3950 3.8353 1e-04
#> monthapr 1 0.2165 0.2381 0.9091 0.3633
#> monthsep 1 1.6722 0.3912 4.2751 0.0000
#> duration 1 0.0044 2e-04 20.7105 0.0000
#> campaign 1 -0.0828 0.0304 -2.7264 0.0064
#> poutcomefailure 1 -0.0716 0.1859 -0.3853 0.7000
#> poutcomeother 1 0.4949 0.2523 1.9612 0.0499
#> poutcomesuccess 1 2.7810 0.2214 12.5604 0.0000
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8201
#> % Discordant 0.0900 Gamma 0.8201
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
#>
#>
#>
#> - default
#>
#> Backward Elimination: Step 5
#>
#> Variable default Removed
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4483 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3088 0.4552 -13.8591 0.0000
#> age 1 0.0076 0.0072 1.0578 0.2901
#> jobtechnician 1 0.0043 0.2075 0.0205 0.9836
#> jobentrepreneur 1 -0.3788 0.3822 -0.9910 0.3217
#> jobblue-collar 1 -0.0891 0.2413 -0.3694 0.7118
#> jobunknown 1 -0.9253 0.9525 -0.9714 0.3314
#> jobretired 1 0.4578 0.3111 1.4716 0.1411
#> jobadmin. 1 0.4029 0.2406 1.6745 0.0940
#> jobservices 1 0.2532 0.2681 0.9447 0.3448
#> jobself-employed 1 -0.0347 0.3126 -0.1110 0.9116
#> jobunemployed 1 -0.3796 0.3800 -0.9991 0.3178
#> jobhousemaid 1 -0.5142 0.4290 -1.1985 0.2307
#> jobstudent 1 0.0576 0.3785 0.1522 0.8790
#> maritalsingle 1 0.4132 0.1443 2.8640 0.0042
#> maritaldivorced 1 -0.1610 0.2071 -0.7773 0.4370
#> educationsecondary 1 -0.3523 0.1711 -2.0585 0.0395
#> educationunknown 1 0.2947 0.3033 0.9718 0.3312
#> educationprimary 1 -0.4138 0.2434 -1.7001 0.0891
#> housingno 1 0.5747 0.1403 4.0970 0.0000
#> loanno 1 0.7109 0.2056 3.4575 5e-04
#> contactcellular 1 1.7099 0.2369 7.2180 0.0000
#> contacttelephone 1 1.3259 0.3260 4.0673 0.0000
#> monthjun 1 0.9644 0.2495 3.8661 1e-04
#> monthjul 1 -0.1080 0.2272 -0.4755 0.6345
#> monthaug 1 -0.2155 0.2382 -0.9049 0.3655
#> monthoct 1 1.5213 0.3346 4.5473 0.0000
#> monthnov 1 -0.1685 0.2448 -0.6885 0.4911
#> monthdec 1 0.9700 0.7726 1.2554 0.2093
#> monthjan 1 -0.6734 0.3596 -1.8725 0.0611
#> monthfeb 1 0.4067 0.2502 1.6255 0.1040
#> monthmar 1 1.5203 0.3950 3.8491 1e-04
#> monthapr 1 0.2207 0.2381 0.9268 0.3540
#> monthsep 1 1.6772 0.3913 4.2866 0.0000
#> duration 1 0.0044 2e-04 20.7131 0.0000
#> campaign 1 -0.0834 0.0304 -2.7471 0.0060
#> poutcomefailure 1 -0.0708 0.1860 -0.3809 0.7033
#> poutcomeother 1 0.4931 0.2521 1.9561 0.0505
#> poutcomesuccess 1 2.7862 0.2214 12.5835 0.0000
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8200
#> % Discordant 0.0900 Gamma 0.8200
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> No more variables satisfy the condition of p value = 0.3
#>
#>
#> Variables Removed:
#>
#> - balance
#> - pdays
#> - day
#> - previous
#> - default
#>
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4483 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3088 0.4552 -13.8591 0.0000
#> age 1 0.0076 0.0072 1.0578 0.2901
#> jobtechnician 1 0.0043 0.2075 0.0205 0.9836
#> jobentrepreneur 1 -0.3788 0.3822 -0.9910 0.3217
#> jobblue-collar 1 -0.0891 0.2413 -0.3694 0.7118
#> jobunknown 1 -0.9253 0.9525 -0.9714 0.3314
#> jobretired 1 0.4578 0.3111 1.4716 0.1411
#> jobadmin. 1 0.4029 0.2406 1.6745 0.0940
#> jobservices 1 0.2532 0.2681 0.9447 0.3448
#> jobself-employed 1 -0.0347 0.3126 -0.1110 0.9116
#> jobunemployed 1 -0.3796 0.3800 -0.9991 0.3178
#> jobhousemaid 1 -0.5142 0.4290 -1.1985 0.2307
#> jobstudent 1 0.0576 0.3785 0.1522 0.8790
#> maritalsingle 1 0.4132 0.1443 2.8640 0.0042
#> maritaldivorced 1 -0.1610 0.2071 -0.7773 0.4370
#> educationsecondary 1 -0.3523 0.1711 -2.0585 0.0395
#> educationunknown 1 0.2947 0.3033 0.9718 0.3312
#> educationprimary 1 -0.4138 0.2434 -1.7001 0.0891
#> housingno 1 0.5747 0.1403 4.0970 0.0000
#> loanno 1 0.7109 0.2056 3.4575 5e-04
#> contactcellular 1 1.7099 0.2369 7.2180 0.0000
#> contacttelephone 1 1.3259 0.3260 4.0673 0.0000
#> monthjun 1 0.9644 0.2495 3.8661 1e-04
#> monthjul 1 -0.1080 0.2272 -0.4755 0.6345
#> monthaug 1 -0.2155 0.2382 -0.9049 0.3655
#> monthoct 1 1.5213 0.3346 4.5473 0.0000
#> monthnov 1 -0.1685 0.2448 -0.6885 0.4911
#> monthdec 1 0.9700 0.7726 1.2554 0.2093
#> monthjan 1 -0.6734 0.3596 -1.8725 0.0611
#> monthfeb 1 0.4067 0.2502 1.6255 0.1040
#> monthmar 1 1.5203 0.3950 3.8491 1e-04
#> monthapr 1 0.2207 0.2381 0.9268 0.3540
#> monthsep 1 1.6772 0.3913 4.2866 0.0000
#> duration 1 0.0044 2e-04 20.7131 0.0000
#> campaign 1 -0.0834 0.0304 -2.7471 0.0060
#> poutcomefailure 1 -0.0708 0.1860 -0.3809 0.7033
#> poutcomeother 1 0.4931 0.2521 1.9561 0.0505
#> poutcomesuccess 1 2.7862 0.2214 12.5835 0.0000
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8200
#> % Discordant 0.0900 Gamma 0.8200
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
#>
#>
#> Elimination Summary
#> -------------------------------------------------------
#> Variable
#> Step Removed AIC BIC Deviance
#> -------------------------------------------------------
#> 1 balance 2166.454 2435.947 2082.4539
#> 2 pdays 2164.602 2427.678 2082.6016
#> 3 day 2162.913 2419.573 2082.9134
#> 4 previous 2161.552 2411.795 2083.5518
#> 5 default 2160.639 2404.465 2084.6387
#> -------------------------------------------------------
Plot
model %>%
blr_step_p_backward() %>%
plot()
#> Backward Elimination Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1 . age
#> 2 . job
#> 3 . marital
#> 4 . education
#> 5 . default
#> 6 . balance
#> 7 . housing
#> 8 . loan
#> 9 . contact
#> 10 . day
#> 11 . month
#> 12 . duration
#> 13 . campaign
#> 14 . pdays
#> 15 . previous
#> 16 . poutcome
#>
#> We are eliminating variables based on p value...
#>
#> Variables Removed:
#>
#> - balance
#> - pdays
#> - day
#> - previous
#> - default
#>
#> No more variables satisfy the condition of p value = 0.3
#>
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4483 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.3088 0.4552 -13.8591 0.0000
#> age 1 0.0076 0.0072 1.0578 0.2901
#> jobtechnician 1 0.0043 0.2075 0.0205 0.9836
#> jobentrepreneur 1 -0.3788 0.3822 -0.9910 0.3217
#> jobblue-collar 1 -0.0891 0.2413 -0.3694 0.7118
#> jobunknown 1 -0.9253 0.9525 -0.9714 0.3314
#> jobretired 1 0.4578 0.3111 1.4716 0.1411
#> jobadmin. 1 0.4029 0.2406 1.6745 0.0940
#> jobservices 1 0.2532 0.2681 0.9447 0.3448
#> jobself-employed 1 -0.0347 0.3126 -0.1110 0.9116
#> jobunemployed 1 -0.3796 0.3800 -0.9991 0.3178
#> jobhousemaid 1 -0.5142 0.4290 -1.1985 0.2307
#> jobstudent 1 0.0576 0.3785 0.1522 0.8790
#> maritalsingle 1 0.4132 0.1443 2.8640 0.0042
#> maritaldivorced 1 -0.1610 0.2071 -0.7773 0.4370
#> educationsecondary 1 -0.3523 0.1711 -2.0585 0.0395
#> educationunknown 1 0.2947 0.3033 0.9718 0.3312
#> educationprimary 1 -0.4138 0.2434 -1.7001 0.0891
#> housingno 1 0.5747 0.1403 4.0970 0.0000
#> loanno 1 0.7109 0.2056 3.4575 5e-04
#> contactcellular 1 1.7099 0.2369 7.2180 0.0000
#> contacttelephone 1 1.3259 0.3260 4.0673 0.0000
#> monthjun 1 0.9644 0.2495 3.8661 1e-04
#> monthjul 1 -0.1080 0.2272 -0.4755 0.6345
#> monthaug 1 -0.2155 0.2382 -0.9049 0.3655
#> monthoct 1 1.5213 0.3346 4.5473 0.0000
#> monthnov 1 -0.1685 0.2448 -0.6885 0.4911
#> monthdec 1 0.9700 0.7726 1.2554 0.2093
#> monthjan 1 -0.6734 0.3596 -1.8725 0.0611
#> monthfeb 1 0.4067 0.2502 1.6255 0.1040
#> monthmar 1 1.5203 0.3950 3.8491 1e-04
#> monthapr 1 0.2207 0.2381 0.9268 0.3540
#> monthsep 1 1.6772 0.3913 4.2866 0.0000
#> duration 1 0.0044 2e-04 20.7131 0.0000
#> campaign 1 -0.0834 0.0304 -2.7471 0.0060
#> poutcomefailure 1 -0.0708 0.1860 -0.3809 0.7033
#> poutcomeother 1 0.4931 0.2521 1.9561 0.0505
#> poutcomesuccess 1 2.7862 0.2214 12.5835 0.0000
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9100 Somers' D 0.8200
#> % Discordant 0.0900 Gamma 0.8200
#> % Tied 0.0000 Tau-a 0.1661
#> Pairs 2070068 c 0.9100
#> ---------------------------------------------------------------
Stepwise Selection
Selection Summary
blr_step_p_both(model)
#> Stepwise Selection Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1. age
#> 2. job
#> 3. marital
#> 4. education
#> 5. default
#> 6. balance
#> 7. housing
#> 8. loan
#> 9. contact
#> 10. day
#> 11. month
#> 12. duration
#> 13. campaign
#> 14. pdays
#> 15. previous
#> 16. poutcome
#>
#> We are selecting variables based on p value...
#>
#> Variables Entered/Removed:
#>
#> - duration added
#> - poutcome added
#> - month added
#> - contact added
#> - housing added
#> - loan added
#> - campaign added
#> - marital added
#> - education added
#> - age added
#>
#> No more variables to be added/removed.
#>
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4494 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.4500 0.4220 -15.2834 0.0000
#> duration 1 0.0043 2e-04 20.6728 0.0000
#> poutcomefailure 1 -0.0607 0.1848 -0.3286 0.7424
#> poutcomeother 1 0.4960 0.2501 1.9829 0.0474
#> poutcomesuccess 1 2.8061 0.2193 12.7976 0.0000
#> monthjun 1 0.9457 0.2497 3.7878 2e-04
#> monthjul 1 -0.1077 0.2248 -0.4791 0.6319
#> monthaug 1 -0.2323 0.2353 -0.9871 0.3236
#> monthoct 1 1.5139 0.3301 4.5867 0.0000
#> monthnov 1 -0.2024 0.2428 -0.8336 0.4045
#> monthdec 1 1.1022 0.7666 1.4377 0.1505
#> monthjan 1 -0.6857 0.3538 -1.9383 0.0526
#> monthfeb 1 0.3908 0.2481 1.5750 0.1152
#> monthmar 1 1.5948 0.3935 4.0524 1e-04
#> monthapr 1 0.2393 0.2366 1.0115 0.3118
#> monthsep 1 1.7156 0.3810 4.5032 0.0000
#> contactcellular 1 1.7353 0.2371 7.3195 0.0000
#> contacttelephone 1 1.3093 0.3235 4.0477 1e-04
#> housingno 1 0.5636 0.1364 4.1307 0.0000
#> loanno 1 0.6997 0.2043 3.4243 6e-04
#> campaign 1 -0.0861 0.0302 -2.8505 0.0044
#> maritalsingle 1 0.4474 0.1423 3.1449 0.0017
#> maritaldivorced 1 -0.1397 0.2051 -0.6809 0.4959
#> educationsecondary 1 -0.2693 0.1313 -2.0512 0.0402
#> educationunknown 1 0.2768 0.2802 0.9880 0.3232
#> educationprimary 1 -0.4408 0.1981 -2.2251 0.0261
#> age 1 0.0116 0.0061 1.8920 0.0585
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9082 Somers' D 0.8164
#> % Discordant 0.0918 Gamma 0.8164
#> % Tied 0.0000 Tau-a 0.1654
#> Pairs 2070068 c 0.9082
#> ---------------------------------------------------------------
#>
#> Stepwise Selection Summary
#> --------------------------------------------------------------------
#> Added/
#> Step Variable Removed AIC BIC C(p)
#> --------------------------------------------------------------------
#> 1 duration addition 2674.384 2687.217 2670.3840
#> 2 poutcome addition 2396.014 2428.097 2386.0140
#> 3 month addition 2274.109 2376.773 2242.1090
#> 4 contact addition 2207.884 2323.381 2171.8840
#> 5 housing addition 2184.550 2306.463 2146.5500
#> 6 loan addition 2171.972 2300.302 2131.9720
#> 7 campaign addition 2164.164 2298.910 2122.1640
#> 8 marital addition 2158.524 2306.103 2112.5240
#> 9 education addition 2155.837 2322.666 2103.8370
#> 10 age addition 2154.272 2327.517 2100.2720
#> --------------------------------------------------------------------
Detailed Output
blr_step_p_both(model, details = TRUE)
#> Stepwise Selection Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1. age
#> 2. job
#> 3. marital
#> 4. education
#> 5. default
#> 6. balance
#> 7. housing
#> 8. loan
#> 9. contact
#> 10. day
#> 11. month
#> 12. duration
#> 13. campaign
#> 14. pdays
#> 15. previous
#> 16. poutcome
#>
#> We are selecting variables based on p value...
#>
#>
#> Stepwise Selection: Step 1
#>
#> - duration added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4519 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> ------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> ------------------------------------------------------------------
#> (Intercept) 1 -3.2978 0.0858 -38.4526 0.0000
#> duration 1 0.0037 2e-04 20.8847 0.0000
#> ------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.8181 Somers' D 0.6379
#> % Discordant 0.1809 Gamma 0.6372
#> % Tied 0.0010 Tau-a 0.1291
#> Pairs 2070068 c 0.8186
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Stepwise Selection: Step 2
#>
#> - poutcome added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4516 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> ----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> ----------------------------------------------------------------------
#> (Intercept) 1 -3.7304 0.1036 -36.0223 0.0000
#> duration 1 0.0039 2e-04 20.8282 0.0000
#> poutcomefailure 1 0.4597 0.1662 2.7658 0.0057
#> poutcomeother 1 0.9144 0.2289 3.9955 1e-04
#> poutcomesuccess 1 3.3439 0.2027 16.4967 0.0000
#> ----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.8606 Somers' D 0.7219
#> % Discordant 0.1390 Gamma 0.7216
#> % Tied 5e-04 Tau-a 0.1462
#> Pairs 2070068 c 0.8608
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Stepwise Selection: Step 3
#>
#> - month added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4505 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> ----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> ----------------------------------------------------------------------
#> (Intercept) 1 -4.4977 0.1634 -27.5205 0.0000
#> duration 1 0.0041 2e-04 20.9764 0.0000
#> poutcomefailure 1 0.2289 0.1802 1.2704 0.2039
#> poutcomeother 1 0.7266 0.2434 2.9851 0.0028
#> poutcomesuccess 1 3.1614 0.2114 14.9534 0.0000
#> monthjun 1 0.7262 0.2107 3.4457 6e-04
#> monthjul 1 0.6399 0.1998 3.2024 0.0014
#> monthaug 1 0.8630 0.1996 4.3238 0.0000
#> monthoct 1 2.5665 0.3144 8.1627 0.0000
#> monthnov 1 0.6606 0.2256 2.9278 0.0034
#> monthdec 1 2.1451 0.7506 2.8578 0.0043
#> monthjan 1 0.3876 0.3335 1.1621 0.2452
#> monthfeb 1 1.3033 0.2288 5.6964 0.0000
#> monthmar 1 2.7631 0.3727 7.4144 0.0000
#> monthapr 1 0.9654 0.2273 4.2480 0.0000
#> monthsep 1 2.7023 0.3513 7.6917 0.0000
#> ----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.8935 Somers' D 0.7870
#> % Discordant 0.1065 Gamma 0.7870
#> % Tied 0.0000 Tau-a 0.1594
#> Pairs 2070068 c 0.8935
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Stepwise Selection: Step 4
#>
#> - contact added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4503 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -5.5654 0.2425 -22.9480 0.0000
#> duration 1 0.0042 2e-04 20.9910 0.0000
#> poutcomefailure 1 -0.1050 0.1823 -0.5759 0.5647
#> poutcomeother 1 0.3955 0.2444 1.6182 0.1056
#> poutcomesuccess 1 2.8860 0.2146 13.4492 0.0000
#> monthjun 1 1.3006 0.2362 5.5070 0.0000
#> monthjul 1 -0.1192 0.2160 -0.5521 0.5809
#> monthaug 1 0.1103 0.2128 0.5184 0.6042
#> monthoct 1 2.0192 0.3187 6.3356 0.0000
#> monthnov 1 -0.0239 0.2344 -0.1018 0.9189
#> monthdec 1 1.5531 0.7546 2.0582 0.0396
#> monthjan 1 -0.2942 0.3389 -0.8681 0.3853
#> monthfeb 1 0.6446 0.2367 2.7233 0.0065
#> monthmar 1 2.0912 0.3783 5.5285 0.0000
#> monthapr 1 0.3072 0.2340 1.3125 0.1893
#> monthsep 1 2.2170 0.3625 6.1152 0.0000
#> contactcellular 1 1.8567 0.2338 7.9423 0.0000
#> contacttelephone 1 1.5399 0.3153 4.8844 0.0000
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9016 Somers' D 0.8032
#> % Discordant 0.0984 Gamma 0.8032
#> % Tied 0.0000 Tau-a 0.1627
#> Pairs 2070068 c 0.9016
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Stepwise Selection: Step 5
#>
#> - housing added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4502 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -5.6760 0.2452 -23.1446 0.0000
#> duration 1 0.0043 2e-04 20.8730 0.0000
#> poutcomefailure 1 -0.0518 0.1838 -0.2816 0.7783
#> poutcomeother 1 0.4490 0.2475 1.8144 0.0696
#> poutcomesuccess 1 2.8664 0.2168 13.2208 0.0000
#> monthjun 1 0.9695 0.2463 3.9363 1e-04
#> monthjul 1 -0.3280 0.2211 -1.4838 0.1379
#> monthaug 1 -0.3194 0.2303 -1.3871 0.1654
#> monthoct 1 1.6413 0.3263 5.0305 0.0000
#> monthnov 1 -0.2138 0.2408 -0.8881 0.3745
#> monthdec 1 1.1017 0.7773 1.4174 0.1564
#> monthjan 1 -0.6787 0.3519 -1.9287 0.0538
#> monthfeb 1 0.3840 0.2450 1.5675 0.1170
#> monthmar 1 1.7452 0.3884 4.4938 0.0000
#> monthapr 1 0.2601 0.2353 1.1054 0.2690
#> monthsep 1 1.8475 0.3744 4.9345 0.0000
#> contactcellular 1 1.8156 0.2342 7.7534 0.0000
#> contacttelephone 1 1.4055 0.3171 4.4318 0.0000
#> housingno 1 0.6643 0.1331 4.9895 0.0000
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9068 Somers' D 0.8137
#> % Discordant 0.0931 Gamma 0.8137
#> % Tied 0.0000 Tau-a 0.1649
#> Pairs 2070068 c 0.9069
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Stepwise Selection: Step 6
#>
#> - loan added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4501 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -6.3293 0.3120 -20.2832 0.0000
#> duration 1 0.0042 2e-04 20.7811 0.0000
#> poutcomefailure 1 -0.0535 0.1841 -0.2906 0.7714
#> poutcomeother 1 0.4863 0.2484 1.9577 0.0503
#> poutcomesuccess 1 2.8391 0.2176 13.0491 0.0000
#> monthjun 1 0.9747 0.2469 3.9479 1e-04
#> monthjul 1 -0.2046 0.2232 -0.9168 0.3592
#> monthaug 1 -0.3488 0.2307 -1.5119 0.1306
#> monthoct 1 1.6098 0.3267 4.9271 0.0000
#> monthnov 1 -0.1809 0.2409 -0.7510 0.4526
#> monthdec 1 1.1086 0.7861 1.4103 0.1585
#> monthjan 1 -0.6682 0.3538 -1.8884 0.0590
#> monthfeb 1 0.4145 0.2453 1.6893 0.0912
#> monthmar 1 1.7041 0.3899 4.3708 0.0000
#> monthapr 1 0.2712 0.2357 1.1503 0.2500
#> monthsep 1 1.8237 0.3755 4.8568 0.0000
#> contactcellular 1 1.8250 0.2349 7.7696 0.0000
#> contacttelephone 1 1.3811 0.3181 4.3415 0.0000
#> housingno 1 0.6489 0.1334 4.8659 0.0000
#> loanno 1 0.7245 0.2010 3.6036 3e-04
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9078 Somers' D 0.8156
#> % Discordant 0.0922 Gamma 0.8156
#> % Tied 0.0000 Tau-a 0.1652
#> Pairs 2070068 c 0.9078
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Stepwise Selection: Step 7
#>
#> - campaign added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4500 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -6.1334 0.3178 -19.2999 0.0000
#> duration 1 0.0043 2e-04 20.6910 0.0000
#> poutcomefailure 1 -0.0755 0.1836 -0.4112 0.6809
#> poutcomeother 1 0.4827 0.2486 1.9418 0.0522
#> poutcomesuccess 1 2.7964 0.2178 12.8371 0.0000
#> monthjun 1 0.9922 0.2470 4.0167 1e-04
#> monthjul 1 -0.1316 0.2241 -0.5873 0.5570
#> monthaug 1 -0.2420 0.2332 -1.0378 0.2994
#> monthoct 1 1.5741 0.3278 4.8022 0.0000
#> monthnov 1 -0.1844 0.2402 -0.7674 0.4429
#> monthdec 1 1.0838 0.7741 1.4000 0.1615
#> monthjan 1 -0.7119 0.3547 -2.0072 0.0447
#> monthfeb 1 0.4247 0.2457 1.7286 0.0839
#> monthmar 1 1.6952 0.3912 4.3332 0.0000
#> monthapr 1 0.2480 0.2358 1.0518 0.2929
#> monthsep 1 1.8103 0.3753 4.8239 0.0000
#> contactcellular 1 1.7993 0.2341 7.6856 0.0000
#> contacttelephone 1 1.4005 0.3181 4.4020 0.0000
#> housingno 1 0.6303 0.1335 4.7206 0.0000
#> loanno 1 0.7440 0.2015 3.6913 2e-04
#> campaign 1 -0.0872 0.0305 -2.8597 0.0042
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9078 Somers' D 0.8157
#> % Discordant 0.0922 Gamma 0.8157
#> % Tied 0.0000 Tau-a 0.1653
#> Pairs 2070068 c 0.9078
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Stepwise Selection: Step 8
#>
#> - marital added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4498 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -----------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -----------------------------------------------------------------------
#> (Intercept) 1 -6.2166 0.3232 -19.2362 0.0000
#> duration 1 0.0043 2e-04 20.6977 0.0000
#> poutcomefailure 1 -0.0618 0.1840 -0.3358 0.7370
#> poutcomeother 1 0.4844 0.2484 1.9502 0.0512
#> poutcomesuccess 1 2.7988 0.2186 12.8055 0.0000
#> monthjun 1 1.0072 0.2480 4.0613 0.0000
#> monthjul 1 -0.1173 0.2242 -0.5233 0.6008
#> monthaug 1 -0.1957 0.2343 -0.8353 0.4036
#> monthoct 1 1.5696 0.3278 4.7882 0.0000
#> monthnov 1 -0.1667 0.2413 -0.6909 0.4896
#> monthdec 1 1.1235 0.7726 1.4541 0.1459
#> monthjan 1 -0.6885 0.3536 -1.9472 0.0515
#> monthfeb 1 0.4190 0.2461 1.7027 0.0886
#> monthmar 1 1.6821 0.3913 4.2987 0.0000
#> monthapr 1 0.2403 0.2364 1.0167 0.3093
#> monthsep 1 1.7938 0.3768 4.7608 0.0000
#> contactcellular 1 1.7598 0.2347 7.4973 0.0000
#> contacttelephone 1 1.4023 0.3183 4.4051 0.0000
#> housingno 1 0.6240 0.1341 4.6540 0.0000
#> loanno 1 0.7328 0.2029 3.6122 3e-04
#> campaign 1 -0.0848 0.0303 -2.8016 0.0051
#> maritalsingle 1 0.3566 0.1256 2.8387 0.0045
#> maritaldivorced 1 -0.1138 0.2031 -0.5603 0.5753
#> -----------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9074 Somers' D 0.8148
#> % Discordant 0.0926 Gamma 0.8148
#> % Tied 0.0000 Tau-a 0.1651
#> Pairs 2070068 c 0.9074
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Stepwise Selection: Step 9
#>
#> - education added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4495 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -5.9983 0.3447 -17.4009 0.0000
#> duration 1 0.0043 2e-04 20.6767 0.0000
#> poutcomefailure 1 -0.0483 0.1844 -0.2619 0.7934
#> poutcomeother 1 0.5010 0.2493 2.0096 0.0445
#> poutcomesuccess 1 2.8168 0.2190 12.8614 0.0000
#> monthjun 1 0.9698 0.2485 3.9021 1e-04
#> monthjul 1 -0.1035 0.2247 -0.4606 0.6451
#> monthaug 1 -0.2130 0.2348 -0.9069 0.3645
#> monthoct 1 1.5774 0.3282 4.8063 0.0000
#> monthnov 1 -0.1724 0.2420 -0.7123 0.4763
#> monthdec 1 1.1275 0.7682 1.4677 0.1422
#> monthjan 1 -0.6652 0.3520 -1.8901 0.0587
#> monthfeb 1 0.4108 0.2475 1.6598 0.0970
#> monthmar 1 1.6334 0.3911 4.1765 0.0000
#> monthapr 1 0.2538 0.2365 1.0730 0.2833
#> monthsep 1 1.7658 0.3796 4.6515 0.0000
#> contactcellular 1 1.7250 0.2365 7.2926 0.0000
#> contacttelephone 1 1.3868 0.3196 4.3396 0.0000
#> housingno 1 0.6103 0.1339 4.5565 0.0000
#> loanno 1 0.7056 0.2043 3.4536 6e-04
#> campaign 1 -0.0858 0.0302 -2.8450 0.0044
#> maritalsingle 1 0.3269 0.1270 2.5736 0.0101
#> maritaldivorced 1 -0.1032 0.2032 -0.5081 0.6114
#> educationsecondary 1 -0.2625 0.1312 -2.0002 0.0455
#> educationunknown 1 0.3202 0.2793 1.1465 0.2516
#> educationprimary 1 -0.3637 0.1929 -1.8851 0.0594
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9075 Somers' D 0.8151
#> % Discordant 0.0924 Gamma 0.8151
#> % Tied 0.0000 Tau-a 0.1651
#> Pairs 2070068 c 0.9075
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> Stepwise Selection: Step 10
#>
#> - age added
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4494 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.4500 0.4220 -15.2834 0.0000
#> duration 1 0.0043 2e-04 20.6728 0.0000
#> poutcomefailure 1 -0.0607 0.1848 -0.3286 0.7424
#> poutcomeother 1 0.4960 0.2501 1.9829 0.0474
#> poutcomesuccess 1 2.8061 0.2193 12.7976 0.0000
#> monthjun 1 0.9457 0.2497 3.7878 2e-04
#> monthjul 1 -0.1077 0.2248 -0.4791 0.6319
#> monthaug 1 -0.2323 0.2353 -0.9871 0.3236
#> monthoct 1 1.5139 0.3301 4.5867 0.0000
#> monthnov 1 -0.2024 0.2428 -0.8336 0.4045
#> monthdec 1 1.1022 0.7666 1.4377 0.1505
#> monthjan 1 -0.6857 0.3538 -1.9383 0.0526
#> monthfeb 1 0.3908 0.2481 1.5750 0.1152
#> monthmar 1 1.5948 0.3935 4.0524 1e-04
#> monthapr 1 0.2393 0.2366 1.0115 0.3118
#> monthsep 1 1.7156 0.3810 4.5032 0.0000
#> contactcellular 1 1.7353 0.2371 7.3195 0.0000
#> contacttelephone 1 1.3093 0.3235 4.0477 1e-04
#> housingno 1 0.5636 0.1364 4.1307 0.0000
#> loanno 1 0.6997 0.2043 3.4243 6e-04
#> campaign 1 -0.0861 0.0302 -2.8505 0.0044
#> maritalsingle 1 0.4474 0.1423 3.1449 0.0017
#> maritaldivorced 1 -0.1397 0.2051 -0.6809 0.4959
#> educationsecondary 1 -0.2693 0.1313 -2.0512 0.0402
#> educationunknown 1 0.2768 0.2802 0.9880 0.3232
#> educationprimary 1 -0.4408 0.1981 -2.2251 0.0261
#> age 1 0.0116 0.0061 1.8920 0.0585
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9082 Somers' D 0.8164
#> % Discordant 0.0918 Gamma 0.8164
#> % Tied 0.0000 Tau-a 0.1654
#> Pairs 2070068 c 0.9082
#> ---------------------------------------------------------------
#>
#>
#>
#>
#> No more variables to be added/removed.
#>
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4494 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.4500 0.4220 -15.2834 0.0000
#> duration 1 0.0043 2e-04 20.6728 0.0000
#> poutcomefailure 1 -0.0607 0.1848 -0.3286 0.7424
#> poutcomeother 1 0.4960 0.2501 1.9829 0.0474
#> poutcomesuccess 1 2.8061 0.2193 12.7976 0.0000
#> monthjun 1 0.9457 0.2497 3.7878 2e-04
#> monthjul 1 -0.1077 0.2248 -0.4791 0.6319
#> monthaug 1 -0.2323 0.2353 -0.9871 0.3236
#> monthoct 1 1.5139 0.3301 4.5867 0.0000
#> monthnov 1 -0.2024 0.2428 -0.8336 0.4045
#> monthdec 1 1.1022 0.7666 1.4377 0.1505
#> monthjan 1 -0.6857 0.3538 -1.9383 0.0526
#> monthfeb 1 0.3908 0.2481 1.5750 0.1152
#> monthmar 1 1.5948 0.3935 4.0524 1e-04
#> monthapr 1 0.2393 0.2366 1.0115 0.3118
#> monthsep 1 1.7156 0.3810 4.5032 0.0000
#> contactcellular 1 1.7353 0.2371 7.3195 0.0000
#> contacttelephone 1 1.3093 0.3235 4.0477 1e-04
#> housingno 1 0.5636 0.1364 4.1307 0.0000
#> loanno 1 0.6997 0.2043 3.4243 6e-04
#> campaign 1 -0.0861 0.0302 -2.8505 0.0044
#> maritalsingle 1 0.4474 0.1423 3.1449 0.0017
#> maritaldivorced 1 -0.1397 0.2051 -0.6809 0.4959
#> educationsecondary 1 -0.2693 0.1313 -2.0512 0.0402
#> educationunknown 1 0.2768 0.2802 0.9880 0.3232
#> educationprimary 1 -0.4408 0.1981 -2.2251 0.0261
#> age 1 0.0116 0.0061 1.8920 0.0585
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9082 Somers' D 0.8164
#> % Discordant 0.0918 Gamma 0.8164
#> % Tied 0.0000 Tau-a 0.1654
#> Pairs 2070068 c 0.9082
#> ---------------------------------------------------------------
#>
#> Stepwise Selection Summary
#> --------------------------------------------------------------------
#> Added/
#> Step Variable Removed AIC BIC C(p)
#> --------------------------------------------------------------------
#> 1 duration addition 2674.384 2687.217 2670.3840
#> 2 poutcome addition 2396.014 2428.097 2386.0140
#> 3 month addition 2274.109 2376.773 2242.1090
#> 4 contact addition 2207.884 2323.381 2171.8840
#> 5 housing addition 2184.550 2306.463 2146.5500
#> 6 loan addition 2171.972 2300.302 2131.9720
#> 7 campaign addition 2164.164 2298.910 2122.1640
#> 8 marital addition 2158.524 2306.103 2112.5240
#> 9 education addition 2155.837 2322.666 2103.8370
#> 10 age addition 2154.272 2327.517 2100.2720
#> --------------------------------------------------------------------
Plot
model %>%
blr_step_p_both() %>%
plot()
#> Stepwise Selection Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1. age
#> 2. job
#> 3. marital
#> 4. education
#> 5. default
#> 6. balance
#> 7. housing
#> 8. loan
#> 9. contact
#> 10. day
#> 11. month
#> 12. duration
#> 13. campaign
#> 14. pdays
#> 15. previous
#> 16. poutcome
#>
#> We are selecting variables based on p value...
#>
#> Variables Entered/Removed:
#>
#> - duration added
#> - poutcome added
#> - month added
#> - contact added
#> - housing added
#> - loan added
#> - campaign added
#> - marital added
#> - education added
#> - age added
#>
#> No more variables to be added/removed.
#>
#>
#> Final Model Output
#> ------------------
#>
#> - Creating model overview.
#> - Creating response profile.
#> - Extracting maximum likelihood estimates.
#> - Estimating concordant and discordant pairs.
#> Model Overview
#> ------------------------------------------------------------------------
#> Data Set Resp Var Obs. Df. Model Df. Residual Convergence
#> ------------------------------------------------------------------------
#> data y 4521 4520 4494 TRUE
#> ------------------------------------------------------------------------
#>
#> Response Summary
#> --------------------------------------------------------
#> Outcome Frequency Outcome Frequency
#> --------------------------------------------------------
#> 0 4004 1 517
#> --------------------------------------------------------
#>
#> Maximum Likelihood Estimates
#> -------------------------------------------------------------------------
#> Parameter DF Estimate Std. Error z value Pr(>|z|)
#> -------------------------------------------------------------------------
#> (Intercept) 1 -6.4500 0.4220 -15.2834 0.0000
#> duration 1 0.0043 2e-04 20.6728 0.0000
#> poutcomefailure 1 -0.0607 0.1848 -0.3286 0.7424
#> poutcomeother 1 0.4960 0.2501 1.9829 0.0474
#> poutcomesuccess 1 2.8061 0.2193 12.7976 0.0000
#> monthjun 1 0.9457 0.2497 3.7878 2e-04
#> monthjul 1 -0.1077 0.2248 -0.4791 0.6319
#> monthaug 1 -0.2323 0.2353 -0.9871 0.3236
#> monthoct 1 1.5139 0.3301 4.5867 0.0000
#> monthnov 1 -0.2024 0.2428 -0.8336 0.4045
#> monthdec 1 1.1022 0.7666 1.4377 0.1505
#> monthjan 1 -0.6857 0.3538 -1.9383 0.0526
#> monthfeb 1 0.3908 0.2481 1.5750 0.1152
#> monthmar 1 1.5948 0.3935 4.0524 1e-04
#> monthapr 1 0.2393 0.2366 1.0115 0.3118
#> monthsep 1 1.7156 0.3810 4.5032 0.0000
#> contactcellular 1 1.7353 0.2371 7.3195 0.0000
#> contacttelephone 1 1.3093 0.3235 4.0477 1e-04
#> housingno 1 0.5636 0.1364 4.1307 0.0000
#> loanno 1 0.6997 0.2043 3.4243 6e-04
#> campaign 1 -0.0861 0.0302 -2.8505 0.0044
#> maritalsingle 1 0.4474 0.1423 3.1449 0.0017
#> maritaldivorced 1 -0.1397 0.2051 -0.6809 0.4959
#> educationsecondary 1 -0.2693 0.1313 -2.0512 0.0402
#> educationunknown 1 0.2768 0.2802 0.9880 0.3232
#> educationprimary 1 -0.4408 0.1981 -2.2251 0.0261
#> age 1 0.0116 0.0061 1.8920 0.0585
#> -------------------------------------------------------------------------
#>
#> Association of Predicted Probabilities and Observed Responses
#> ---------------------------------------------------------------
#> % Concordant 0.9082 Somers' D 0.8164
#> % Discordant 0.0918 Gamma 0.8164
#> % Tied 0.0000 Tau-a 0.1654
#> Pairs 2070068 c 0.9082
#> ---------------------------------------------------------------
