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Statistical rethinking : a Bayesian course with examples in R and Stan / Richard McElreath, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

Author
McElreath, Richard, 1973-
Published
Boca Raton : CRC Press/Taylor & Francis Group, [2016]
Physical Description
xvii, 469 pages : illustrations ; 27 cm.

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Contents
Machine generated contents note: ch. 1 The Golem of Prague -- 1.1.Statistical golems -- 1.2.Statistical rethinking -- 1.3.Three tools for golem engineering -- 1.4.Summary -- ch. 2 Small Worlds and Large Worlds -- 2.1.The garden of forking data -- 2.2.Building a model -- 2.3.Components of the model -- 2.4.Making the model go -- 2.5.Summary -- 2.6.Practice -- ch. 3 Sampling the Imaginary -- 3.1.Sampling from a grid-approximate posterior -- 3.2.Sampling to summarize -- 3.3.Sampling to simulate prediction -- 3.4.Summary -- 3.5.Practice -- ch. 4 Linear Models -- 4.1.Why normal distributions are normal -- 4.2.A language for describing models -- 4.3.A Gaussian model of height -- 4.4.Adding a predictor -- 4.5.Polynomial regression -- 4.6.Summary -- 4.7.Practice -- ch. 5 Multivariate Linear Models -- 5.1.Spurious association -- 5.2.Masked relationship -- 5.3.When adding variables hurts -- 5.4.Categorical variables -- 5.5.Ordinary least squares and Im -- 5.6.Summary -- 5.7.Practice -- ch. 6 Overfitting, Regularization, and Information Criteria -- 6.1.The problem with parameters -- 6.2.Information theory and model performance -- 6.3.Regularization -- 6.4.Information criteria -- 6.5.Using information criteria -- 6.6.Summary -- 6.7.Practice -- ch. 7 Interactions -- 7.1.Building an interaction -- 7.2.Symmetry of the linear interaction -- 7.3.Continuous interactions -- 7.4.Interactions in design formulas -- 7.5.Summary -- 7.6.Practice -- ch. 8 Markov Chain Monte Carlo -- 8.1.Good King Markov and His island kingdom -- 8.2.Markov chain Monte Carlo -- 8.3.Easy HMC: map2stan -- 8.4.Care and feeding of your Markov chain -- 8.5.Summary -- 8.6.Practice -- ch. 9 Big Entropy and the Generalized Linear Model -- 9.1.Maximum entropy -- 9.2.Generalized linear models -- 9.3.Maximum entropy priors -- 9.4.Summary -- ch. 10 Counting and Classification -- 10.1.Binomial regression -- 10.2.Poisson regression -- 10.3.Other count regressions -- 10.4.Summary -- 10.5.Practice -- ch. 11 Monsters and Mixtures -- 11.1.Ordered categorical outcomes -- 11.2.Zero-inflated outcomes -- 11.3.Over-dispersed outcomes -- 11.4.Summary -- 11.5.Practice -- ch. 12 Multilevel Models -- 12.1.Example: Multilevel tadpoles -- 12.2.Varying effects and the underfitting/overfitting trade-off -- 12.3.More than one type of cluster -- 12.4.Multilevel posterior predictions -- 12.5.Summary -- 12.6.Practice -- ch. 13 Adventures in Covariance -- 13.1.Varying slopes by construction -- 13.2.Example: Admission decisions and gender -- 13.3.Example: Cross-classified chimpanzees with varying slopes -- 13.4.Continuous categories and the Gaussian process -- 13.5.Summary -- 13.6.Practice -- ch. 14 Missing Data and Other Opportunities -- 14.1.Measurement error -- 14.2.Missing data -- 14.3.Summary -- 14.4.Practice -- ch. 15 Horoscopes.
Subject(s)
ISBN
9781482253443 (hardcover : alk. paper)
1482253445 (hardcover : alk. paper)
Note
"A CRC title."
Bibliography Note
Includes bibliographical references and index.
View MARC record | catkey: 17502795