Regression analysis of hierarchical Poisson-like event rate data
superpopulation model effect on predictions
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Author
Contributions
- Jacobs, Patricia A. - Contributor
- O'Muircheartaigh, I. G. - Contributor
- Naval Postgraduate School (U.S.). Dept. of Operations Research - Contributor
Publication
1990 - Naval Postgraduate School, Monterey, Calif, California
Language
English
Word Count
4,750 words, Guess
Page Count
19 pages
Identifiers
- Internet Archiveregressionanalys00gave
- Open LibraryOL33206379M
Alternate Titles
- NPS-55-90-19.
Description
This paper studies prediction of future failure (rates) by hierarchical empirical Bayes (EB) Poisson regression methodologies. Both a gamma distributed super-population as well as a more robust (long-tailed) log student- t super-population are considered. Simulation results are reported concerning predicted Poisson rates. The results tentatively suggest that a hierarchical model with gamma super-population can effectively adapt to data coming from a log-Student-t-super-population particularly if the additional computation involved with estimation for the log-Student-t hierarchical model is burdensome.
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