Statistical Rethinking: A Bayesian Course With Examples In R And STAN Chapman

From a straightforward Bayesian perspective that draws on information theory and maximum entropy, the text presents causal inference and generalized linear multilevel models. From the fundamentals of regression to advanced multilevel models, the core material covers them all. In addition, it provides Gaussian process models for spatial and phylogenetic confounding, measurement error, and missing data.