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Statistical Rethinking: A Bayesian Course with Examples in R and STAN by McElreath, Richard; is a nonfiction available to read on EtoBox.

What is Statistical Rethinking: A Bayesian Course with Examples in R and STAN about?

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today’s model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work. The text presents causal inference and generalized linear multilevel models from a simple Bayesian perspective that builds on information theory and maximum entropy. The core material ranges from the basics of regression to advanced multilevel models. It also presents measurement error, missing data, and Gaussian process models for spatial and phylogenetic confounding. The second edition emphasizes the directed acyclic graph (DAG) approach to causal inference, integrating DAGs into many examples. The new edition also contains new material on the design of prior distributions, splines, ordered categorical predictors, social relations models, cross-validation, importance sampling, instrumental variables, and Hamiltonian Monte Carlo. It e

Who reads Statistical Rethinking: A Bayesian Course with Examples in R and STAN?

Author

McElreath, Richard;

Publisher

CRC Press LLC

Published

2020

Language

EN

Category

nonfiction

Subjects

Mathematics, Mathematical Statistics, Stem