Random parameter Markov population process models and their likelihood, Bayes, and empirical Bayes analysis
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Author
Contributions
- Lehoczky, John P. - Contributor
- Naval Postgraduate School (U.S.). Dept. of Operations Research - Contributor
Publication
1985 - Naval Postgraduate School, Monterey, Calif, California
Language
English
Word Count
6,000 words, Guess
Page Count
24 pages
Identifiers
- Internet Archiverandomparameterm00gave
- Open LibraryOL25461328M
Alternate 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)
Subjects
Topics
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