Lecture
Binary Response: Link Functions
Related lectures (52)
Binary Responses: Link Functions and GLMs
Explores link functions for binary responses and the impact of sparseness on model interpretability.
Logistic Regression: Probability Mapping
Explains logistic regression, mapping predictions to probabilities and optimizing likelihood.
Survival Data Analysis
Delves into survival data analysis, exploring modeling times until events and applications in various fields.
Mixtures: introductionMOOC: Selected Topics on Discrete Choice
Introduces mixtures, covers discrete and continuous mixtures, explores examples, and discusses combining probit and logit models.
Optimal Errors and Phase Transitions in Generalized Linear Models
Covers optimal errors, phase transitions, and algorithm performance in linear models.
Deterministic Part: Utility Function CodingMOOC: Introduction to Discrete Choice Models
Explores coding behavioral assumptions into a linear-in-parameter utility function.
Mixture models: summaryMOOC: Selected Topics on Discrete Choice
Summarizes mixtures of logit models, covering various mixing methods and modeling techniques for taste heterogeneity.
Panel data: static modelMOOC: Selected Topics on Discrete Choice
Introduces the static model for panel data analysis and discusses its limitations.
Derivation of the logit modelMOOC: Introduction to Discrete Choice Models
Delves into the logit model's derivation, emphasizing the importance of the independence assumption and parameter normalization during estimation.
Choice Models: Logit Model Derivation
Covers the derivation of the logit model for choice with multiple alternatives and the challenges in generating choice sets.