Dynamic Probabilistic Systems, Volume I

Markov Models

Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book Dynamic Probabilistic Systems, Volume I by Ronald A. Howard, Dover Publications
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Author: Ronald A. Howard ISBN: 9780486140674
Publisher: Dover Publications Publication: May 4, 2012
Imprint: Dover Publications Language: English
Author: Ronald A. Howard
ISBN: 9780486140674
Publisher: Dover Publications
Publication: May 4, 2012
Imprint: Dover Publications
Language: English
This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory.
Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, begins with the basic Markov model, proceeding to systems analyses of linear processes and Markov processes, transient Markov processes and Markov process statistics, and statistics and inference. Subsequent chapters explore recurrent events and random walks, Markovian population models, and time-varying Markov processes. Volume I concludes with a pair of helpful indexes.
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory.
Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, begins with the basic Markov model, proceeding to systems analyses of linear processes and Markov processes, transient Markov processes and Markov process statistics, and statistics and inference. Subsequent chapters explore recurrent events and random walks, Markovian population models, and time-varying Markov processes. Volume I concludes with a pair of helpful indexes.

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