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Author : James John Martin
Publisher :
ISBN 13 :
Total Pages : 510 pages
Book Rating : 4.:/5 (242 download)
Download or read book Some Bayesian Decision Problems in a Markov Chain written by James John Martin and published by . This book was released on 1965 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : James John Martin
Publisher :
ISBN 13 :
Total Pages : 224 pages
Book Rating : 4.F/5 ( download)
Download or read book Bayesian Decision Problems and Markov Chains written by James John Martin and published by . This book was released on 1967 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book ... deals with a theoretical foundation for the solution of decision problems in a Markov chain with uncertain transition probabilities and considers both sequential sampling and fixed-sample-size problems." -- Preface.
Author : James J. Martin
Publisher :
ISBN 13 :
Total Pages : 202 pages
Book Rating : 4.:/5 (17 download)
Download or read book BAYESIAN DECISION PROBLEMS AND MARKOV CHAINS written by James J. Martin and published by . This book was released on 1975 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Juan José Martín González
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (83 download)
Download or read book Bayesian Decision Problems and Markov Chains written by Juan José Martín González and published by . This book was released on 1967 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Erdal Panayirci
Publisher :
ISBN 13 :
Total Pages : 308 pages
Book Rating : 4.3/5 (129 download)
Download or read book Bayesian Decision Making and Learning for Continuous-time Markov Systems written by Erdal Panayirci and published by . This book was released on 1970 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: The document is concerned with Bayesian decision making and learning algorithms for a particular problem in parametric pattern recognition in which each of a finite set of pattern classes is characterized by a continuous-time, discrete-state Markov process. The basic problem considered is that of determining rules for making decisions about the identity of the active pattern class based upon observation of a sample function in some finite interval. The stationary transition probability matrices for the processes in question are the parameters of the pattern classes. (Author).
Author : James John Martin
Publisher :
ISBN 13 :
Total Pages : 224 pages
Book Rating : 4.F/5 ( download)
Download or read book Bayesian Decision Problems and Markov Chains written by James John Martin and published by . This book was released on 1967 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book ... deals with a theoretical foundation for the solution of decision problems in a Markov chain with uncertain transition probabilities and considers both sequential sampling and fixed-sample-size problems." -- Preface.
Author : Wen-Lin Lai
Publisher :
ISBN 13 :
Total Pages : 214 pages
Book Rating : 4.:/5 (319 download)
Download or read book Admissibility of Formal Bayes Inferences in Quadratically Regular Decision Problems written by Wen-Lin Lai and published by . This book was released on 1996 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Thomas Dyhre Nielsen
Publisher : Springer Science & Business Media
ISBN 13 : 0387682821
Total Pages : 457 pages
Book Rating : 4.3/5 (876 download)
Download or read book Bayesian Networks and Decision Graphs written by Thomas Dyhre Nielsen and published by Springer Science & Business Media. This book was released on 2009-03-17 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical models including Bayesian networks and influence diagrams. The reader is guided through the two types of frameworks with examples and exercises, which also give instruction on how to build these models. Structured in two parts, the first section focuses on probabilistic graphical models, while the second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision process and partially ordered decision problems.
Author : Dani Gamerman
Publisher : CRC Press
ISBN 13 : 9781584885870
Total Pages : 352 pages
Book Rating : 4.8/5 (858 download)
Download or read book Markov Chain Monte Carlo written by Dani Gamerman and published by CRC Press. This book was released on 2006-05-10 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : H. M. Dietz
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3112733398
Total Pages : 176 pages
Book Rating : 4.1/5 (127 download)
Download or read book Markov Decision Problems with Countable State Spaces written by H. M. Dietz and published by Walter de Gruyter GmbH & Co KG. This book was released on 1984-01-14 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Markov Decision Problems with Countable State Spaces".
Author : James J. Martin
Publisher :
ISBN 13 :
Total Pages : 202 pages
Book Rating : 4.:/5 (85 download)
Download or read book Bayesian Decision Problems and Marcov Chains written by James J. Martin and published by . This book was released on 1975 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : William Ross Osgood
Publisher :
ISBN 13 :
Total Pages : 89 pages
Book Rating : 4.:/5 (249 download)
Download or read book Bayesian Decision Theory Applied to the Finite State Markov Decision Problem written by William Ross Osgood and published by . This book was released on 1971 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : William Ross Osgood
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (249 download)
Download or read book Bayesian Decision Theory Applied to the Finite State Markov Decision Problem written by William Ross Osgood and published by . This book was released on 1971 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Dani Gamerman
Publisher : CRC Press
ISBN 13 : 9780412818202
Total Pages : 264 pages
Book Rating : 4.8/5 (182 download)
Download or read book Markov Chain Monte Carlo written by Dani Gamerman and published by CRC Press. This book was released on 1997-10-01 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridging the gap between research and application, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference provides a concise, and integrated account of Markov chain Monte Carlo (MCMC) for performing Bayesian inference. This volume, which was developed from a short course taught by the author at a meeting of Brazilian statisticians and probabilists, retains the didactic character of the original course text. The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians. It describes each component of the theory in detail and outlines related software, which is of particular benefit to applied scientists.
Author :
Publisher :
ISBN 13 :
Total Pages : 574 pages
Book Rating : 4.3/5 (91 download)
Download or read book NBS Special Publication written by and published by . This book was released on 1970 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Richard C. Dubes
Publisher :
ISBN 13 :
Total Pages : 34 pages
Book Rating : 4.:/5 (227 download)
Download or read book Bayesian Learning in Markov Chains with Observable States written by Richard C. Dubes and published by . This book was released on 1969 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two practical and related problems concerning decision-making with observations from Markov chains are considered in this report. First, Bayesian learning theory is used to develop recursive relations for the densities of the unknown parameters in a Markov chain, based on classified observations of the chain's states. Computationally simple results are obtained using a matrix-beta distribution for the chain's parameters. In the case of unsupervised observations, the basic relations for learning are derived and methods for their implementation are discussed. Second, the related problem of deciding which of a set of chains is active, based on state observations, is considered. Two data-generating models are proposed and decision rules are derived. A particularly useful result is derived for one model using the matrix-beta distribution for the unknown parameters. The decision rule for the more difficult model is then derived and its implications discussed. Simulation results for a specific example show the probability of error for different amounts of training data and demonstrate the inherent practicality of the results. (Author).
Author : Roger Hartley
Publisher :
ISBN 13 :
Total Pages : 360 pages
Book Rating : 4.X/5 (1 download)
Download or read book Recent Developments in Markov Decision Processes written by Roger Hartley and published by . This book was released on 1980 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt:
