An edition of Random parameter Markov population process models and their likelihood, Bayes, and empirical Bayes analysis
(1985)
Random parameter Markov population process models and their likelihood, Bayes, and empirical Bayes analysis
by Donald Paul Gaver
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Markov population stochastic processes are useful in describing repairman and logistics problems, networks of queues, pharmacological processes, and manpower situations. This paper considers statistical estimation problems arising for such mathematical models. Parameter estimation of an empirical Bayes nature, with limited shrinkage or discrepancy tolerant features is discussed and illustrated. Additional keywords: Maximum likelihood estimation; Pharmacology; Statistical inference; Statistical analysis. (Author)
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Random parameter Markov population process models and their likelihood, Bayes, and empirical Bayes analysis
1985, Naval Postgraduate School, Available from National Technical Information Service
in English
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Book Details
Edition Notes
Title from cover.
"NPS-55-85-020."
"September 1985."
AD A159 812.
Includes bibliographical references (p. 15-16).
aq/aq cc:9116 05/28/98
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