Handbook of Markov Chain Monte Carlo

ISBN 13 : 9781420079418

Handbook of Markov Chain Monte Carlo

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9781420079418: Handbook of Markov Chain Monte Carlo

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Présentation de l'éditeur :

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.

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Jones, Galin L. (edt); Brooks, Steve (edt); Meng, Xiao-Li (edt); Gelman, Andrew (edt)
ISBN 10 : 1420079417 ISBN 13 : 9781420079418
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Edité par Taylor Francis Ltd, United States (2011)
ISBN 10 : 1420079417 ISBN 13 : 9781420079418
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Description du livre Taylor Francis Ltd, United States, 2011. Hardback. État : New. 236 x 155 mm. Language: English . Brand New Book. 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. N° de réf. du libraire AA69781420079418

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Edité par Taylor Francis Ltd, United States (2011)
ISBN 10 : 1420079417 ISBN 13 : 9781420079418
Neuf(s) Couverture rigide Quantité : 10
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The Book Depository
(London, Royaume-Uni)
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Description du livre Taylor Francis Ltd, United States, 2011. Hardback. État : New. 236 x 155 mm. Language: English . Brand New Book. 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. N° de réf. du libraire AA69781420079418

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Steve Brooks
Edité par Chapman and Hall/CRC (2011)
ISBN 10 : 1420079417 ISBN 13 : 9781420079418
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Description du livre Chapman and Hall/CRC, 2011. HRD. État : New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. N° de réf. du libraire FT-9781420079418

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Brooks, Steve (EDT)/ Gelman, Andrew (EDT)/ Jones, Galin L. (EDT)/ Meng, Xiao-Li (EDT)
Edité par Taylor & Francis Ltd 2011-05-13 (2011)
ISBN 10 : 1420079417 ISBN 13 : 9781420079418
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Blackwell's
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Description du livre Taylor & Francis Ltd 2011-05-13, 2011. hardback. État : New. N° de réf. du libraire 9781420079418

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Brooks, Steve
Edité par Taylor Fransis
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Steve Brooks, Andrew Gelman, Galin Jones, Xiao-Li Meng
ISBN 10 : 1420079417 ISBN 13 : 9781420079418
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Ria Christie Collections
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Description du livre Hardback. État : New. Not Signed; 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 aston. book. N° de réf. du libraire ria9781420079418_rkm

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Andrew Gelman
ISBN 10 : 1420079417 ISBN 13 : 9781420079418
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Description du livre 2011. Hardcover. État : New. 178mm x 254mm x 33mm. Hardcover. 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 Bay.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 619 pages. 1.262. N° de réf. du libraire 9781420079418

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Steve Brooks
Edité par Chapman and Hall/CRC (2011)
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Description du livre Chapman and Hall/CRC, 2011. HRD. État : New. New Book.Shipped from US within 10 to 14 business days. Established seller since 2000. N° de réf. du libraire IB-9781420079418

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Brooks, Steve (Edited by)/ Gelman, Andrew (Edited by)/ Jones, Galin (Edited by)/ Meng, Xiao-Li (Edited by)
Edité par Chapman & Hall (2010)
ISBN 10 : 1420079417 ISBN 13 : 9781420079418
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Revaluation Books
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Description du livre Chapman & Hall, 2010. Hardcover. État : Brand New. 1st edition. 619 pages. 10.16x7.24x1.34 inches. In Stock. N° de réf. du libraire __1420079417

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