Bayesian Methods for Statistical Analysis
Overview & Synopsis
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of lectures and one tutorial per week for 13 weeks.
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Document Information
| Document Title | Bayesian Methods for Statistical Analysis |
|---|---|
| Author / Organization | Puza, Borek |
| Subject & Discipline | statistics |
| Categories | Open Access Books |
| Publication Year | 2021 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
Directory of Open Access Books
(www.doabooks.org)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-165151 |
| Original Source Link | Visit Source Page on www.doabooks.org » |