Random parameter Markov population process models and their likelihood, Bayes, and empirical Bayes analysis
By: by Donald P. Gaver, John P. Lehoczky
Contributors: Lehoczky, John P.; Naval Postgraduate School (U.S.). Dept. of Operations Research
Publisher: Naval Postgraduate School; Available from National Technical Information Service
Published: 1985
Place of publication: Monterey, Calif; Springfield, Va
Language: eng
Number of pages: 24
Subjects: MATHEMATICAL MODELS; POPULATION(MATHEMATICS); MARKOV PROCESSES
Other titles: NPS-55-85-020.
Description: 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)
Notes: Title from cover.

"NPS-55-85-020."

"September 1985."

AD A159 812.

Includes bibliographical references (p. 15-16).

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