A first course in Bayesian statistical methods / Peter D. Hoff.
Material type:
Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds |
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EWU Library E-book | Non-fiction | 519.5 HOF 2009 (Browse shelf(Opens below)) | Not for loan | ||||
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EWU Library Reserve Section | Non-fiction | 519.5 HOF 2009 (Browse shelf(Opens below)) | C-1 | Not For Loan | 26679 |
Includes bibliographical references (p. [259]-265) and index.
TOC 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.
AS
Tahur Ahmed
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