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

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Authors
Gaver, Donald Paul
Lehoczky, John P.
Subjects
Markov processes
likelihood estimation
empirical Bayes
Advisors
Date of Issue
1985-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
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Abstract
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)
Type
Technical Report
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https://hdl.handle.net/10945/30122
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NPS Report Number
NPS55-85-020
Sponsors
Office of Naval Research.
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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