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Handbook of Markov chain Monte Carlo /
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton ; London :
CRC Press,
©2011.
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| Colección: | Chapman & Hall/CRC handbooks of modern statistical methods.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Handbook of Markov chain Monte Carlo / |c edited by Steve Brooks [and others]. |
| 264 | 1 | |a Boca Raton ; |a London : |b CRC Press, |c ©2011. | |
| 300 | |a 1 online resource (xxv, 592 pages) : |b illustrations, maps | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Chapman & Hall/CRC handbooks of modern statistical methods | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | 0 | |t Foundations, methodology, and algorithms. |t Introduction to Markov chain Monte Carlo / |r Charles J. Geyer ; |t A short history of MCMC : |t subjective recollections from incomplete data / |r Christian Robert and George Casella ; |t Reversible jump MCMC / |r Yanan Fan and Scott A. Sisson ; |t Optimal proposal distributions and adaptive MCMC / |r Jeffrey S. Rosenthal ; |t MCMC using Hamiltonian dynamics / |r Radford M. Neal ; |t Inference from simulations and monitoring convergence / |r Andrew Gelman and Kenneth Shirley ; |t Implementing MCMC : |t estimating with confidence / |r James M. Flegal and Galin L. Jones ; |t Perfection within reach : |t exact MCMC sampling / |r Radu V. Craiu and Xiao-Li Meng ; |t Spatial point processes / |r Mark Huber ; |t The data augmentation algorithm : |t theory and methodology / |r James P. Hobert ; |t Importance sampling, simulated tempering, and umbrella sampling / |r Charles J. Geyer ; |t Likelihood-free MCMC / |r Scott A. Sisson and Yanan Fan -- |t Applications and case studies. |t MCMC in the analysis of genetic data on related individuals / |r Elizabeth Thompson ; |t An MCMC-based analysis of a multilevel model for functional MRI data / |r Brian Caffo [and others] ; |t Partially collapsed Gibbs sampling and path-adaptive metropolis-Hastings in high-energy astrophysics / |r David A. van Dyk and Taeyoung Park ; |t Posterior exploration for computationally intensive forward models / |r David Higdon [and others] ; |t Statistical ecology / |r Ruth King ; |t Gaussian random field models for spatial data / |r Murali Haran ; |t Modeling preference changes via a hidden Markov item response theory model / |r Jong Hee Park ; |t Parallel Bayesian MCMC imputation for multiple distributed lag models : |t a case study in environmental epidemiology / |r Biran Caffo [and others] ; |t MCMC for state-space models / |r Paul Fearnhead ; |t MCMC in educational research / |r Roy Levy, Robert J. Mislevy, and John T. Behrens -- |t Applications of MCMC in fisheries science / |r Russell B. Millar ; |t Model comparison and simulation for hierarchical models : |t analyzing rural-urban migration in Thailand / |r Filiz Garip and Bruce Western. |
| 520 | |a 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 referenc. | ||
| 546 | |a English. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Monte Carlo method. | |
| 650 | 0 | |a Monte Carlo method |v Case studies. | |
| 650 | 0 | |a Markov processes. | |
| 650 | 0 | |a Markov processes |v Case studies. | |
| 650 | 2 | |a Monte Carlo Method | |
| 650 | 2 | |a Markov Chains | |
| 650 | 6 | |a Méthode de Monte-Carlo. | |
| 650 | 6 | |a Méthode de Monte-Carlo |v Études de cas. | |
| 650 | 6 | |a Processus de Markov. | |
| 650 | 6 | |a Processus de Markov |v Études de cas. | |
| 650 | 7 | |a Markov processes |2 fast | |
| 650 | 7 | |a Monte Carlo method |2 fast | |
| 650 | 7 | |a Monte-Carlo-Simulation |2 gnd | |
| 650 | 7 | |a Markov-Algorithmus |2 gnd | |
| 650 | 7 | |a Markov-Prozess |2 gnd | |
| 655 | 0 | |a Electronic books. | |
| 655 | 2 | |a Case Reports | |
| 655 | 7 | |a handbooks. |2 aat | |
| 655 | 7 | |a Case studies |2 fast | |
| 655 | 7 | |a Case studies. |2 lcgft | |
| 655 | 7 | |a Handbooks and manuals. |2 lcgft | |
| 655 | 7 | |a Études de cas. |2 rvmgf | |
| 655 | 7 | |a Guides et manuels. |2 rvmgf | |
| 700 | 1 | |a Brooks, Steve, |d 1970- |e editor. |1 https://id.oclc.org/worldcat/entity/E39PBJfx8PFc7wGpDRdT6ymGHC | |
| 758 | |i has work: |a Handbook of Markov chain Monte Carlo (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGcqvcmDp73cJHF3v9F8BX |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |t Handbook of Markov chain Monte Carlo. |d Boca Raton ; London : CRC Press, ©2011 |z 9781420079418 |w (OCoLC)540161452 |
| 830 | 0 | |a Chapman & Hall/CRC handbooks of modern statistical methods. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=762505 |z Texto completo |
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