| Document Type
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BL
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| Record Number
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841473
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| Main Entry
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Broemeling, Lyle D.
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| Title & Author
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Bayesian inference for stochastic processes /\ Lyle D. Broemeling.
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| Edition Statement
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First edition.
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| Publication Statement
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Boca Raton, FL :: CRC Press,, [2018]
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, ©2018
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| Page. NO
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1 online resource (xv, 432 pages)
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| ISBN
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1315303566
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: 1315303574
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: 1315303582
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: 1315303590
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: 9781315303567
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: 9781315303574
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: 9781315303581
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: 9781315303598
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1138196134
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9781138196131
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Introduction to Bayesian inference for stochastic processes -- Bayesian analysis -- Introduction to stochastic processes -- Bayesian inference for discrete Markov chains -- Examples of Markov chains in biology -- Inferences for Markov chains in continuous time -- Bayesian inference: examples of continuous-time Markov chains -- Bayesian inferences for normal processes -- Queues and time series.
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| Abstract
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"The book aims to introduce Bayesian inference methods for stochastic processes. The Bayesian approach has advantages compared to non-Bayesian, among which is the optimal use of prior information via data from previous similar experiments. Examples from biology, economics, and astronomy reinforce the basic concepts of the subject. R and WinBUGS."--Provided by publisher.
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| Subject
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Bayesian statistical decision theory.
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Probabilities.
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| Subject
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Stochastic processes.
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Bayesian statistical decision theory.
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MATHEMATICS-- Applied.
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MATHEMATICS-- Probability Statistics-- General.
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| Subject
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Probabilities.
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| Subject
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Stochastic processes.
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| Dewey Classification
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519.22
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| LC Classification
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QA273
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