10.4. R/Python Code

On our code page, we provide a comprehensive illustration of various aspects related to logistic regression modeling. Specifically, we cover how to fit a logistic regression model, interpret coefficients, compute deviance, make predictions using logit and probability, and perform variable selection.

We offer code for the analysis of the Phoneme Dataset (Chap 5.2.3 from ESL), where we model logistic regression coefficients using natural cubic splines.