10 Logistic Regression
Learning objectives:
- Gain a deeper understanding of logistic regression
- Show existence and uniqueness of optimal solution
- Motivate and perform robust logistic regression
- Motivate and perform Bayesian logistic regression
- Motivate and perform probit regression
library("bayesplot")
library("broom.mixed")
library("dplyr")
library("janitor")
library("ggplot2")
library("ggtext")
library("robust")
library("rstanarm")
library("palmerpenguins")Session Info
## R version 4.4.0 (2024-04-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.4 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
##
## locale:
## [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
## [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
## [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
## [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
##
## time zone: UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] palmerpenguins_0.1.1 rstanarm_2.32.1 Rcpp_1.0.12
## [4] robust_0.7-4 fit.models_0.64 broom.mixed_0.2.9.5
## [7] bayesplot_1.11.1 tidyr_1.3.1 patchwork_1.2.0
## [10] magrittr_2.0.3 janitor_2.2.0 gt_0.10.1
## [13] ggtext_0.1.2 ggplot2_3.5.1 e1071_1.7-14
## [16] dplyr_1.1.4 bayesrules_0.0.2
##
## loaded via a namespace (and not attached):
## [1] tensorA_0.36.2.1 jsonlite_1.8.8 farver_2.1.2
## [4] nloptr_2.0.3 rmarkdown_2.27 vctrs_0.6.5
## [7] minqa_1.2.7 base64enc_0.1-3 htmltools_0.5.8.1
## [10] forcats_1.0.0 distributional_0.4.0 curl_5.2.1
## [13] broom_1.0.6 sass_0.4.9 parallelly_1.37.1
## [16] StanHeaders_2.32.9 bslib_0.7.0 htmlwidgets_1.6.4
## [19] plyr_1.8.9 zoo_1.8-12 lubridate_1.9.3
## [22] cachem_1.1.0 commonmark_1.9.1 igraph_2.0.3
## [25] mime_0.12 lifecycle_1.0.4 pkgconfig_2.0.3
## [28] colourpicker_1.3.0 Matrix_1.7-0 R6_2.5.1
## [31] fastmap_1.2.0 future_1.33.2 shiny_1.8.1.1
## [34] snakecase_0.11.1 digest_0.6.35 colorspace_2.1-0
## [37] furrr_0.3.1 crosstalk_1.2.1 labeling_0.4.3
## [40] fansi_1.0.6 timechange_0.3.0 abind_1.4-5
## [43] compiler_4.4.0 proxy_0.4-27 withr_3.0.0
## [46] backports_1.5.0 inline_0.3.19 shinystan_2.6.0
## [49] QuickJSR_1.2.0 pkgbuild_1.4.4 highr_0.11
## [52] MASS_7.3-60.2 gtools_3.9.5 loo_2.7.0
## [55] tools_4.4.0 rrcov_1.7-5 httpuv_1.6.15
## [58] threejs_0.3.3 glue_1.7.0 nlme_3.1-164
## [61] promises_1.3.0 gridtext_0.1.5 grid_4.4.0
## [64] checkmate_2.3.1 reshape2_1.4.4 generics_0.1.3
## [67] gtable_0.3.5 class_7.3-22 xml2_1.3.6
## [70] utf8_1.2.4 pillar_1.9.0 markdown_1.12
## [73] stringr_1.5.1 posterior_1.5.0 later_1.3.2
## [76] robustbase_0.99-2 splines_4.4.0 lattice_0.22-6
## [79] survival_3.5-8 tidyselect_1.2.1 miniUI_0.1.1.1
## [82] knitr_1.47 gridExtra_2.3 V8_4.4.2
## [85] bookdown_0.39 groupdata2_2.0.3 stats4_4.4.0
## [88] xfun_0.44 matrixStats_1.3.0 DEoptimR_1.1-3
## [91] DT_0.33 rstan_2.32.6 stringi_1.8.4
## [94] yaml_2.3.8 boot_1.3-30 evaluate_0.23
## [97] codetools_0.2-20 tibble_3.2.1 cli_3.6.2
## [100] RcppParallel_5.1.7 shinythemes_1.2.0 xtable_1.8-4
## [103] munsell_0.5.1 jquerylib_0.1.4 globals_0.16.3
## [106] parallel_4.4.0 rstantools_2.4.0 dygraphs_1.1.1.6
## [109] lme4_1.1-35.3 listenv_0.9.1 mvtnorm_1.2-5
## [112] scales_1.3.0 xts_0.13.2 pcaPP_2.0-4
## [115] purrr_1.0.2 rlang_1.1.3 shinyjs_2.1.0