Doing Bayesian data analysis : a tutorial with R, JAGS, and Stan / John K. Kruschke, Dept. of Psychological and Brain Sciences, Indiana University, Bloomington

By:

Kruschke, John K [VerfasserIn]

Resource type: Ressourcentyp: BuchBookLanguage: English Publisher: Amsterdam ; Boston ; Heidelberg ; London ; New York ; Oxford ; Paris ; San Diego ; San Francisco ; Singapore ; Sydney ; Tokyo : Elsevier, Academic Press, [2015]Copyright date: © 2015Edition: Edition 2Description: xii, 759 Seiten : Illustrationen, Diagramme ; 25 cmISBN:

9780124058880

Subject(s): Genre/Form:

Lehrbuch

Additional physical formats: Erscheint auch als: Doing Bayesian data analysis. Online-Ausgabe. 2nd Edition. Amsterdam [u.a.] : AP, Academic Press/Elsevier, 2015. Online Ressource (v, 759 pages) | Erscheint auch als: Doing Bayesian data analysis. Online-Ausgabe Edition 2. Amsterdam : Elsevier, Academic Press, 2015. 1 Online-Ressource (xii, 759 pages)MSC: MSC: *62-01 | 62-07 | 62C12 | 62F15 | 62F03 | 62J10 | 62H12 | 62H17RVK: RVK: CM 4400 | ST 250 | ST 601 | QH 233 | SK 830LOC classification:

QA279.5

NLM classification:

QA 279.5

Summary: 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 dataSummary: 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 -- IndexCall number: Grundsignatur: 2017 A 6133(2)PPN: PPN: 78816645X

Holdings ( 1 )

Holdings
Item type	Home library	Shelving location	Call number	Status	Date due	Barcode	Item holds
Magazinbestand ausleihbar	Bibliothek Campus Süd	Geschlossenes Magazin	2017 A 6133(2)	Available		53136451090

Total holds: 0