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Bayesian statistical modelling

Author: P Congdon
Publisher: Chichester, England ; Hoboken, NJ : John Wiley & Sons, ©2006.
Series: Wiley series in probability and statistics.
Edition/Format:   eBook : Document : English : 2nd edView all editions and formats
Summary:
Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and the use of new sampling methods for estimating parameters.
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Congdon, P.
Bayesian statistical modelling.
Chichester, England ; Hoboken, NJ : John Wiley & Sons, ©2006
(DLC) 2006023990
(OCoLC)70673258
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: P Congdon
ISBN: 9780470035931 0470035935 9780470035948 0470035943
OCLC Number: 128344136
Description: 1 online resource (xi, 573 pages) : illustrations.
Contents: Introduction : the Bayesian method, its benefits and implementation --
Bayesian model choice, comparison and checking --
The major densities and their application --
Normal linear regression, general linear models and log-linear models --
Hierarchical priors for pooling strength and overdispersed regression modelling --
Discrete mixture priors --
Multinomial and ordinal regression models --
Time series models --
Modelling spatial dependencies --
Nonlinear and nonparametric regression --
Multilevel and panel data models --
Latent variable and structural equation models for multivariate data --
Survival and event history analysis --
Missing data models --
Measurement error, seemingly unrelated regressions, and simultaneous eqations.
Series Title: Wiley series in probability and statistics.
Responsibility: Peter Congdon.
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Abstract:

Bayesian Statistical Modelling, Second Edition, provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets.  Read more...

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"This text is ideal for researchers in applied statistics, medical sciences, public health and the social sciences, who will benefit greatly from the examples and applications featured. The book will Read more...

 
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