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Applied Bayesian modelling / Peter Congdon.

By: Congdon, PMaterial type: TextTextLanguage: English Publication details: Chichester, West Sussex : Wiley ; c2014 Edition: 2nd edDescription: ix, 437 p. : ill. ; 25 cmISBN: 9781119951513 (cloth); 1119951518Subject(s): Bayesian statistical decision theory | Mathematical statisticsDDC classification: 519.542 LOC classification: QA279.5 | .C649 2014Online resources: WorldCat details | E-book Fulltext
Contents:
Bayesian methods and Bayesian estimation -- Hierarchical models for related units -- Regression techniques -- More advanced regression techniques -- Meta-analysis and multilevel models -- Models for time series -- Analysis of panel data -- Models for spatial outcomes and geographical association -- Latent variable and structural equation models -- Survival and event history models.
Summary: Summary: <p>This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets.
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
E-Book E-Book Dr. S. R. Lasker Library, EWU
E-book 		Non-fiction 519.542 COA 2014 (Browse shelf(Opens below)) Not For Loan
Text Text Dr. S. R. Lasker Library, EWU
Reserve Section 		Non-fiction 519.542 COA 2014 (Browse shelf(Opens below)) C-1 Not For Loan 26513
Text Text Dr. S. R. Lasker Library, EWU
Reserve Section 		Non-fiction 519.542 COA 2014 (Browse shelf(Opens below)) C-2 Not For Loan 26646
Total holds: 0

Online version:
Congdon, P.
Applied Bayesian modelling
Chichester, West Sussex : John Wiley & Sons, Inc., 2014
(DLC) 2014011504

Includes bibliographical references and index.

Bayesian methods and Bayesian estimation -- Hierarchical models for related units -- Regression techniques -- More advanced regression techniques -- Meta-analysis and multilevel models -- Models for time series -- Analysis of panel data -- Models for spatial outcomes and geographical association -- Latent variable and structural equation models -- Survival and event history models.

Summary:
<p>This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets.

AS

Saifun Momota

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