Generalized Linear Models

Related lectures (30)

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Provides an overview of Generalized Linear Models, focusing on logistic and Poisson regression models, and their implementation in R.

Covers regression with exponential family responses using Generalised Linear Models.

Explores Generalized Linear Regression, Classification, confusion matrices, ROC curves, and noise in data.

Covers the analysis of chimpanzee data on learning times and explores generalized linear models and logistic regression.

Explores the IRLS algorithm for weighted least squares estimation in GLM.

Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.

Explores model selection criteria like AIC, BIC, and Cp in statistics for data science.

Introduces the basics of supervised learning, focusing on logistic regression, linear classification, and likelihood maximization.

Explores the impact of a binary covariate on binary responses using 2x2 tables.

Introduces the fundamentals of supervised learning, including loss functions and probability distributions.