Derivation of the logit modelDelves into the logit model's derivation, emphasizing the importance of the independence assumption and parameter normalization during estimation.
Binary Choice ModelCovers the binary choice model, error term assumptions, specific constants, invariances, and distribution properties.
Logistic Regression: Part 1Introduces logistic regression for binary classification and explores multiclass classification using OvA and OvO strategies.
Derivation of the logit modelExplains the derivation of the logit model in choice models, covering error terms, choice sets, and availability conditions.
