The R-command for all GLM-regressions are collected on R-commands for logistic regression.

For quantile regression, see the lecture R-code.

When	What	Material
Tue 4/5, 8.15-10.00, Zoom	Lecture 10: Wrap up Lecture 7 - 10: Logistic regression. GLM, Poisson distribution and Poisson regression; Negative binomial regression.	Slides: lecture_10_vt21.pdf (updated version with pseudo R2, 29/4) R-code: lecture10_ex1_poisson.R ; lecture10_ex2_negbin.R Extra code for prediction intervals: lecture10_ex1_poisson-predint.R ; lecture10_ex2_negbin-predint.R boot_poisson.R ; boot_negbin.R Data: award_predint.RData ; nb_data.RData ; nb_predint.RData Video: Lecture videos: other regressions
Mon 10/5, 8.15-10.00, Zoom	Lecture 11: more GLM: Multinomial and Ordinal logistic regression. Distribution free: Quantile regression	Slides: lecture_11_vt21.pdf R-code: lecture11_ex1_multinomial.R ; lecture11_ex2_ordinal.R ; lecture11_ex3_quantile.R (bugfix 10/5) Data: hsbdemo.rda ; ologit.rda skewdata.rda Video: Lecture videos: other regressions
Tue 11/5, 8.15-9.00, Zoom	Lecture 12: Wrap up. Advice on the oral exam	Slides: lecture_12_vt21.pdf Video: Lecture videos: other regressions