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Regression analysis of hierarchical poisson-like event rate data: superpopulation model effect on predictions

Gaver, D.P.
; 
Jacobs, P.A.
; 
O'Muircheartaigh, I.G.
Identifiers
http://hdl.handle.net/10379/9203
 https://doi.org/10.13025/24023
Publication Date
1990-01-01
Keywords
empirical bayes prediction, hierarchical models, extra-poisson variability, poisson regression, gamma superpopulation, log student-t superpopulation, empirical bayes
Type
Article
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Citation
Gaver, D.P. Jacobs, P.A.; O'Muircheartaigh, I.G. (1990). Regression analysis of hierarchical poisson-like event rate data: superpopulation model effect on predictions. Communications in Statistics - Theory and Methods 19 (10), 3779-3797
Abstract
This paper studies prediction of future failure (rates) by hierarchical empirical Bayes (EB) Poisson regression methodologies. Both a gamma distributed superpopulation as well as a more robust (long-tailed) log student-t superpopulation are considered. Simulation results are reported concerning predicted Poisson rates. The results tentatively suggest that a hierarchical model with gamma superpopulation can effectively adapt to data coming from a log-Student-t superpopulation particularly if the additional computation involved with estimation for the log-Student-t hierarchical model is burdensome.
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Publisher
Informa UK Limited
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Attribution-NonCommercial-NoDerivs 3.0 Ireland
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Externally hosted open access publications with University of Galway authors (1)