9781584885870 - markov chain monte carlo: stochastic simulation for bayesian inference, second edition di gamerman, dani; lopes, hedibert f. (20 risultati)
Lingua: Inglese
Editore: Chapman and Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Hardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.
Lingua: Inglese
Editore: Chapman and Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Lingua: Inglese
Editore: Chapman and Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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hardcover. Condizione: New. In shrink wrap. Looks like an interesting title.
Lingua: Inglese
Editore: Chapman and Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Lingua: Inglese
Editore: Taylor & Francis Inc 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.
Lingua: Inglese
Editore: Chapman and Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Condizione: New.
Lingua: Inglese
Editore: Chapman and Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Condizione: New. In.
Lingua: Inglese
Editore: Taylor and Francis Inc, US 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Hardback. Condizione: New. While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incorporating changes in theory and highlighting new applications…, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition presents a concise, accessible, and comprehensive introduction to the methods of this valuable simulation technique. The second edition includes access to an internet site that provides the code, written in R and WinBUGS, used in many of the previously existing and new examples and exercises. More importantly, the self-explanatory nature of the codes will enable modification of the inputs to the codes and variation on many directions will be available for further exploration.Major changes from the previous edition: · More examples with discussion of computational details in chapters on Gibbs sampling and Metropolis-Hastings algorithms · Recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection · Discussion of computation using both R and WinBUGS · Additional exercises and selected solutions within the text, with all data sets and software available for download from the Web · Sections on spatial models and model adequacy The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians. The book will appeal to everyone working with MCMC techniques, especially research and graduate statisticians and biostatisticians, and scientists handling data and formulating models. The book has been substantially reinforced as a first reading of material on MCMC and, consequently, as a textbook for modern Bayesian computation and Bayesian inference courses.
Lingua: Inglese
Editore: Chapman and Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Lingua: Inglese
Editore: Chapman and Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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Hardcover. Condizione: Like New. Like New. book.
Lingua: Inglese
Editore: Chapman and Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Lingua: Inglese
Editore: Chapman & Hall 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Hardcover. Condizione: Brand New. 2nd edition. 323 pages. 9.25x6.25x0.75 inches. In Stock.
Lingua: Inglese
Editore: Taylor and Francis Inc, US 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Hardback. Condizione: New. While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incorporating changes in theory and highlighting new applications…, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition presents a concise, accessible, and comprehensive introduction to the methods of this valuable simulation technique. The second edition includes access to an internet site that provides the code, written in R and WinBUGS, used in many of the previously existing and new examples and exercises. More importantly, the self-explanatory nature of the codes will enable modification of the inputs to the codes and variation on many directions will be available for further exploration.Major changes from the previous edition: · More examples with discussion of computational details in chapters on Gibbs sampling and Metropolis-Hastings algorithms · Recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection · Discussion of computation using both R and WinBUGS · Additional exercises and selected solutions within the text, with all data sets and software available for download from the Web · Sections on spatial models and model adequacy The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians. The book will appeal to everyone working with MCMC techniques, especially research and graduate statisticians and biostatisticians, and scientists handling data and formulating models. The book has been substantially reinforced as a first reading of material on MCMC and, consequently, as a textbook for modern Bayesian computation and Bayesian inference courses.
Lingua: Inglese
Editore: Chapman And Hall/CRC Mai 2006 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds.…Incorporating changes in theory and highlighting new applications, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition presents a concise, accessible, and comprehensive introduction to the methods of this valuable simulation technique. The second edition includes access to an internet site that provides the code, written in R and WinBUGS, used in many of the previously existing and new examples and exercises. More importantly, the self-explanatory nature of the codes will enable modification of the inputs to the codes and variation on many directions will be available for further exploration. Major changes from the previous edition: More examples with discussion of computational details in chapters on Gibbs sampling and Metropolis-Hastings algorithms Recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection Discussion of computation using both R and WinBUGS Additional exercises and selected solutions within the text, with all data sets and software available for download from the Web Sections on spatial models and model adequacy The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians. The book will appeal to everyone working with MCMC techniques, especially research and graduate statisticians and biostatisticians, and scientists handling data and formulating models. The book has been substantially reinforced as a first reading of material on MCMC and, consequently, as a textbook for modern Bayesian computation and Bayesian inference courses. 342 pp. Englisch.
Lingua: Inglese
Editore: CRC Press 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Lingua: Inglese
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Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: THE SAINT BOOKSTORE, Southport, , Regno UnitoTHE SAINT BOOKSTORE
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dani Gamerman, Hedibert F. LopesWhile there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the so…lution of inference problems has increased b.
Lingua: Inglese
Editore: Chapman And Hall/CRC 2006
Serie: Chapman & Hall/CRC Texts in Statistical Science, Libro 16 di 59. Libro 16 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incor…porating changes in theory and highlighting new applications, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition presents a concise, accessible, and comprehensive introduction to the methods of this valuable simulation technique. The second edition includes access to an internet site that provides the code, written in R and WinBUGS, used in many of the previously existing and new examples and exercises. More importantly, the self-explanatory nature of the codes will enable modification of the inputs to the codes and variation on many directions will be available for further exploration. Major changes from the previous edition: More examples with discussion of computational details in chapters on Gibbs sampling and Metropolis-Hastings algorithms Recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection Discussion of computation using both R and WinBUGS Additional exercises and selected solutions within the text, with all data sets and software available for download from the Web Sections on spatial models and model adequacy The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians. The book will appeal to everyone working with MCMC techniques, especially research and graduate statisticians and biostatisticians, and scientists handling data and formulating models. The book has been substantially reinforced as a first reading of material on MCMC and, consequently, as a textbook for modern Bayesian computation and Bayesian inference courses.
