Random parameter Markov population process models and their likelihood, Bayes, and empirical Bayes analysis

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July 24, 2014 | History

Random parameter Markov population process models and their likelihood, Bayes, and empirical Bayes analysis

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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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Cover of: Random parameter Markov population process models and their likelihood, Bayes, and empirical Bayes analysis
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

Published in
Monterey, Calif, Springfield, Va
Other Titles
NPS-55-85-020.

The Physical Object

Pagination
24 p. ;
Number of pages
24

ID Numbers

Open Library
OL25461328M
Internet Archive
randomparameterm00gave

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Internet Archive item record

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