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In den WarenkorbHardcover. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 1.4.
Verlag: Chapman & Hall/CRC, Boca Raton, 2006
ISBN 10: 1584885874 ISBN 13: 9781584885870
Sprache: Englisch
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In den WarenkorbHardcover. Second edition. Octavo, xvii, 323 pages. In Very Good condition. Spine is black with white print. Boards in red glossy illustrated paper. Illustrated: b&w graphs, figures. NOTE: Shelved in Netdesk Column P. 1395209. FP New Rockville Stock.
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In den WarenkorbZustand: New. pp. 342.
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In den WarenkorbHardcover. Zustand: Brand New. 2nd edition. 323 pages. 9.25x6.25x0.75 inches. In Stock.
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In den WarenkorbHardcover. Zustand: Like New. Like New. book.
Verlag: Taylor and Francis Inc, US, 2006
ISBN 10: 1584885874 ISBN 13: 9781584885870
Sprache: Englisch
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In den WarenkorbHardback. Zustand: 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.
Verlag: Taylor and Francis Inc, US, 2006
ISBN 10: 1584885874 ISBN 13: 9781584885870
Sprache: Englisch
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes Königreich
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In den WarenkorbHardback. Zustand: 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.
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In den WarenkorbZustand: 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.
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In den WarenkorbZustand: New. pp. 342 Illus. This item is printed on demand.
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In den WarenkorbZustand: New. PRINT ON DEMAND pp. 342.
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In den WarenkorbHardcover. Zustand: Brand New. 2nd edition. 323 pages. 9.25x6.25x0.75 inches. In Stock. This item is printed on demand.