Accession Number:

ADA159812

Title:

Random Parameter Markov Population Process Models and Their Likelihood, Bayes and Empirical Bayes Analysis.

Descriptive Note:

Technical rept.,

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

Report Date:

1985-09-01

Pagination or Media Count:

29.0

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

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE