A first course in Bayesian statistical methods / Peter D. Hoff.
By: Hoff, Peter D
Material type: 





Item type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|---|
![]() |
EWU Library E-book | Non-fiction | 519.5 HOF 2009 (Browse shelf) | Not for loan | ||||
![]() |
EWU Library Reserve Section | Non-fiction | 519.5 HOF 2009 (Browse shelf) | C-1 | Not For Loan | 26679 |
Browsing EWU Library shelves, Shelving location: E-book Close shelf browser
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
||
519.5 DEH 2009 A handbook of statistical analyses using SAS / | 519.5 DIS 2011 Statistics and scientific method : | 519.5 DOI 2008 An introduction to generalized linear models / | 519.5 HOF 2009 A first course in Bayesian statistical methods / | 519.5 HOI 2005 Introduction to mathematical statistics / | 519.5 INT 2017 An introduction to statistical learning : | 519.5 JIL 2007 Linear and generalized linear mixed models and their applications / |
Includes bibliographical references (p. [259]-265) and index.
Table of contents Introduction and examples -- belief, probability and exchangeability -- One-parameter models -- Monte Carlo approximation -- the normal model -- Posterior approximation with the Gibbs sampler -- the multivariate normal model -- Group comparisons and hierarchical modeling -- Linear regression -- Nonconjugate priors and Metropolis-Hastings algorithms -- Linear and generalized linear mixed effects models -- Latent variable methods for ordinal data.
This compact, self-contained introduction to the theory and application of Bayesian statistical methods is accessible to those with a basic familiarity with probability, yet allows advanced readers to grasp the principles underlying Bayesian theory and method.
Applied Statistics
There are no comments for this item.