Beta-binomial/gamma-Poisson regression models for repeated counts with random parameters
Mayra Ivanoff Lora and Julio M. Singer
Source: Braz. J. Probab. Stat. Volume 25, Number 2
(2011), 218-235.
Abstract
Beta-binomial/Poisson models have been used by many authors to model multivariate count data. Lora and Singer [Stat. Med. 27 (2008) 3366–3381] extended such models to accommodate repeated multivariate count data with overdipersion in the binomial component. To overcome some of the limitations of that model, we consider a beta-binomial/gamma-Poisson alternative that also allows for both overdispersion and different covariances between the Poisson counts. We obtain maximum likelihood estimates for the parameters using a Newton–Raphson algorithm and compare both models in a practical example.
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Links and Identifiers
Permanent link to this document: http://projecteuclid.org/euclid.bjps/1301577155
Digital Object Identifier: doi:10.1214/10-BJPS118
Mathematical Reviews number (MathSciNet): MR2793927
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