Doing Bayesian data analysis : a tutorial with R, JAGS, and Stan /
by Kruschke, John K.
Material type:
BookPublisher: Amsterdam : Academic Press, 2015.Edition: 2nd ed.Description: xii, 759 p. : ill. (some col.) ; 24 cm.ISBN: 9780124058880 (hbk).Subject(s): Bayesian statistical decision theory | R (Computer program language) | Electronic booksOnline resources: ScienceDirect | Item type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode |
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Dhaka University Science Library General Stacks | Non Fiction | 519.542 KRD (Browse shelf) | 1 | Available | 518815 | |
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Books
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Dhaka University Science Library General Stacks | Non Fiction | 519.542 KRD (Browse shelf) | 2 | Available | 518816 |
Includes index.
Bibliography : p. 737-745.
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.
Description based on print version record.
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