Accession Number:

ADA230297

Title:

Regression Analysis of Hierarchical Poisson-Like Event Rate Data: Super- Population Model Effect on Predictions

Descriptive Note:

Technical rept.

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

• Gaver, Donald P.
• Jacobs, Patricia A.
• O'Muircheartaigh, I. G.

Report Date:

1990-08-01

Pagination or Media Count:

33.0

Abstract:

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.

Descriptors:

• *SIMULATION
• PREDICTIONS
• MODELS
• POISSON DENSITY FUNCTIONS
• REGRESSION ANALYSIS
• BAYES THEOREM
• HIERARCHIES
• METHODOLOGY
• RATES

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE