£119.60

CRC Press Handbook of Markov Chain Monte Carlo (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)

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Description

Since their popularization in the 1990s, Markov chain Monte Carlo (MCMC) methods have revolutionized statistical computing and have had an especially profound impact on the practice of Bayesian statistics. Furthermore, MCMC methods have enabled the development and use of intricate models in an astonishing array of disciplines as diverse as fisheries science and economics. The wide-ranging practical importance of MCMC has sparked an expansive and deep investigation into fundamental Markov chain theory. The Handbook of Markov Chain Monte Carlo provides a reference for the broad audience of developers and users of MCMC methodology interested in keeping up with cutting-edge theory and applications. The first half of the book covers MCMC foundations, methodology, and algorithms. The second half considers the use of MCMC in a variety of practical applications including in educational research, astrophysics, brain imaging, ecology, and sociology. The in-depth introductory section of the book allows graduate students and practicing scientists new to MCMC to become thoroughly acquainted with the basic theory, algorithms, and applications. The book supplies detailed examples and case studies of realistic scientific problems presenting the diversity of methods used by the wide-ranging MCMC community. Those familiar with MCMC methods will find this book a useful refresher of current theory and recent developments.

Key Features

Handbook of Markov Chain Monte Carlo

Books Subjects Science Nature Maths Biological Sciences Reference Books Subjects Science Nature Maths Mathematics Probability Statistics Books Subjects Science Nature Maths Mathematics Reference Books Subjects Scientific Technical Medical Mathematics Applied Mathematics Statistics Probability Biology

Brand: Chapman and Hall CRC

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
10 May 2011
Listed Since
04 June 2008

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