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Doing Bayesian data analysis : a tutorial with R, JAGS, and Stan / / John K. Kruschke



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Autore: Kruschke John K. Visualizza persona
Titolo: Doing Bayesian data analysis : a tutorial with R, JAGS, and Stan / / John K. Kruschke Visualizza cluster
Pubblicazione: Amsterdam : , : Academic Press is an imprint of Elsevier, , [2015]
©2015
Edizione: Second edition.
Descrizione fisica: 1 online resource (xii, 759 pages ) : illustrations
Disciplina: 519.5/42
Soggetto topico: Bayesian statistical decision theory
R (Computer program language)
Soggetto genere / forma: Electronic books.
Note generali: Bibliographic Level Mode of Issuance: Monograph
Nota di bibliografia: Includes bibliographical references (pages 737-745).
Nota di contenuto: What's in this book (Read this first!) -- Part I The basics: models, probability, Bayes' rule and r: Introduction: credibility, models, and parameters; The R programming language; What is this stuff called probability?; Bayes' rule -- Part II All the fundamentals applied to inferring a binomila probability: Inferring a binomial probability via exact mathematical analysis; Markov chain Monte Carlo; JAGS; Hierarchical models; Model comparison and hierarchical modeling; Null hypothesis significance testing; Bayesian approaches to testing a point ("Null") hypothesis; Goals, power, and sample size; Stan -- Part III The generalized linear model: Overview of the generalized linear model; Metric-predicted variable on one or two groups; Metric predicted variable with one metric predictor; Metric predicted variable with multiple metric predictors; Metric predicted variable with one nominal predictor; Metric predicted variable with multiple nominal predictors; Dichotomous predicted variable; Nominal predicted variable; Ordinal predicted variable; Count predicted variable; Tools in the trunk -- Bibliography -- Index.
Sommario/riassunto: Provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling methods for realistic data.
Titolo autorizzato: Doing bayesian data analysis  Visualizza cluster
ISBN: 0-12-405916-3
0-12-405888-4
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910465133103321
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