Lingua: Inglese
Editore: Chapman and Hall/CRC (edition 2), 2006
ISBN 10: 1584885874 ISBN 13: 9781584885870
Da: BooksRun, Philadelphia, PA, U.S.A.
Hardcover. Condizione: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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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!
Da: Majestic Books, Hounslow, Regno Unito
EUR 82,24
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hardcover. Condizione: New. In shrink wrap. Looks like an interesting title!
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 95,90
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Da: moluna, Greven, Germania
EUR 79,65
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Aggiungi al carrelloCondizione: New. Dani Gamerman: Ph. D. in Statistics from University of Warwick in 1987. Professor of Statistics at UFRJ from 1996 to 2019. Professor Emeritus at UFRJ since 2021. Supervises graduate students and post-doctoral researchers. Author of the .
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 152,22
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Aggiungi al carrelloCondizione: New. In.
Lingua: Inglese
Editore: Taylor and Francis Inc, US, 2006
ISBN 10: 1584885874 ISBN 13: 9781584885870
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 194,15
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Aggiungi al carrelloHardback. 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.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 173,19
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Aggiungi al carrelloHardcover. Condizione: Like New. Like New. book.
Da: Revaluation Books, Exeter, Regno Unito
EUR 197,22
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Aggiungi al carrelloHardcover. Condizione: Brand New. 2nd edition. 323 pages. 9.25x6.25x0.75 inches. In Stock.
Da: Majestic Books, Hounslow, Regno Unito
EUR 205,90
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Da: moluna, Greven, Germania
EUR 190,69
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Aggiungi al carrelloCondizione: New. Dani Gamerman: Ph. D. in Statistics from University of Warwick in 1987. Professor of Statistics at UFRJ from 1996 to 2019. Professor Emeritus at UFRJ since 2021. Supervises graduate students and post-doctoral researchers. Author of the .
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 232,66
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: Taylor and Francis Inc, US, 2006
ISBN 10: 1584885874 ISBN 13: 9781584885870
Da: Rarewaves.com UK, London, Regno Unito
EUR 182,98
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Aggiungi al carrelloHardback. 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.
Da: Basi6 International, Irving, TX, U.S.A.
EUR 102,69
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Aggiungi al carrelloCondizione: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Da: moluna, Greven, Germania
EUR 113,56
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Aggiungi al carrelloGebunden. 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 solution of inference problems has increased b.