Bayesian Statistics and Its Applications

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Satyanshu K. Upadhyay, Umesh Singh, Dipak Dey
Anshan, 2007 - Mathematics - 507 pages
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In the last two decades, Bayesian Statistics has acquired immense importance and has penetrated almost every area including those where the application of statistics appeared to be a remote possibility. This volume provides both theoretical and practical insights into the subject with detailed up-to-date material on various aspects. It serves two important objectives - to offer a thorough background material for theoreticians and gives a variety of applications for applied statisticians and practitioners. Consisting of 33 chapters, it covers topics on biostatistics, econometrics, reliability, image analysis, Bayesian computation, neural networks, prior elicitation, objective Bayesian methodologies, role of randomisation in Bayesian analysis, spatial data analysis, nonparametrics and a lot more. The book will serve as an excellent reference work for updating knowledge and for developing new methodologies in a wide variety of areas. It will become an invaluable tool for statisticians and the practitioners of Bayesian paradigm.

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Contents

Prior Model for Reconstruction of Contingency Table
14
Why Bayesianism? A Primer on a Probabilistic Philosophy of Science
42
On Coregionalized Models for Spatially Replicated Experiments
63
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About the author (2007)

Dept of Statistics, Banaras Hindu University, Varnasi, India

Dept of Statistics, Banaras Hindu University, Varnasi, India

Dept of Statistics, University of Conneticut, Storrs, USA

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