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Practical Nonparametric and Semiparametric Bayesian Statistics

A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparam...

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Bibliographic Details
Other Authors: Dey, Dipak D. (Editor), MüIler, Peter (Editor), Sinha, Debajyoti (Editor)
Format: eBook
Language:English
Published: New York, NY Springer New York 1998, 1998
Edition:1st ed. 1998
Series:Lecture Notes in Statistics
Subjects:
Applied Mathematics
Engineering Mathematics
Applications Of Mathematics
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Description
Summary:A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies
Physical Description:XVI, 392 p online resource
ISBN:9781461217329

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