Matches in Harvard for { <http://id.lib.harvard.edu/aleph/008315738/catalog> ?p ?o. }
Showing items 1 to 25 of
25
with 100 items per page.
- catalog abstract ""This book examines advanced Bayesian computational methods, it presents methods for sampling from posterior distributions and discusses how to compute posterior quantities of interest using Markov Chain Monte Carlo (MCMC) samples. This book examines each of these issues in detail and heavily focuses on computing various posterior summaries from a given MCMC sample." "The book presents and equal mixture of theory and applications involving real data. It is intended as a graduate textbook or a reference book for a one-semester course at the advanced master's or Ph. D. level. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners."--Jacket.".
- catalog contributor b11574052.
- catalog contributor b11574053.
- catalog contributor b11574054.
- catalog created "c2000.".
- catalog date "2000".
- catalog date "c2000.".
- catalog dateCopyrighted "c2000.".
- catalog description ""This book examines advanced Bayesian computational methods, it presents methods for sampling from posterior distributions and discusses how to compute posterior quantities of interest using Markov Chain Monte Carlo (MCMC) samples. This book examines each of these issues in detail and heavily focuses on computing various posterior summaries from a given MCMC sample." "The book presents and equal mixture of theory and applications involving real data. It is intended as a graduate textbook or a reference book for a one-semester course at the advanced master's or Ph. D. level. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners."--Jacket.".
- catalog description "1. Introduction -- 2. Markov Chain Monte Carlo Sampling. 2.1. Gibbs Sampler. 2.2. Metropolis-Hastings Algorithm. 2.3. Hit-and-Run Algorithm. 2.4. Multiple-Try Metropolis Algorithm. 2.5. Grouping, Collapsing, and Reparameterizations. 2.6. Acceleration Algorithms for MCMC Sampling. 2.7. Dynamic Weighting Algorithm. 2.8. Toward "Black-Box" Sampling. 2.9. Convergence Diagnostics -- 3. Basic Monte Carlo Methods for Estimating Posterior Quantities. 3.1. Posterior Quantities. 3.2. Basic Monte Carlo Methods. 3.3. Simulation Standard Error Estimation. 3.4. Improving Monte Carlo Estimates. 3.5. Controlling Simulation Errors -- 4. Estimating Marginal Posterior Densities. 4.1. Marginal Posterior Densities. 4.2. Kernel Methods.".
- catalog description "Includes bibliographical references (p. [356]-374) and indexes.".
- catalog extent "xiii, 386 p. :".
- catalog identifier "0387989358 (hardcover : alk. paper)".
- catalog isPartOf "Springer series in statistics".
- catalog issued "2000".
- catalog issued "c2000.".
- catalog language "eng".
- catalog publisher "New York : Springer,".
- catalog subject "519.5/42 21".
- catalog subject "Bayesian statistical decision theory.".
- catalog subject "Monte Carlo method.".
- catalog subject "QA279.5 .C57 2000".
- catalog tableOfContents "1. Introduction -- 2. Markov Chain Monte Carlo Sampling. 2.1. Gibbs Sampler. 2.2. Metropolis-Hastings Algorithm. 2.3. Hit-and-Run Algorithm. 2.4. Multiple-Try Metropolis Algorithm. 2.5. Grouping, Collapsing, and Reparameterizations. 2.6. Acceleration Algorithms for MCMC Sampling. 2.7. Dynamic Weighting Algorithm. 2.8. Toward "Black-Box" Sampling. 2.9. Convergence Diagnostics -- 3. Basic Monte Carlo Methods for Estimating Posterior Quantities. 3.1. Posterior Quantities. 3.2. Basic Monte Carlo Methods. 3.3. Simulation Standard Error Estimation. 3.4. Improving Monte Carlo Estimates. 3.5. Controlling Simulation Errors -- 4. Estimating Marginal Posterior Densities. 4.1. Marginal Posterior Densities. 4.2. Kernel Methods.".
- catalog title "Monte Carlo methods in Bayesian computation / Ming-Hui Chen, Qi-Man Shao, Joseph G. Ibrahim.".
- catalog type "text".