Semi-parametric extended Poisson process models for count data
(2004) Semi-parametric extended Poisson process models for count data. Statistics and Computing 14(4):pp. 311-321.
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Abstract
A general framework for the analysis of count data (with covariates) is proposed using formulations for the transition rates of a state-dependent birth process. The form for the transition rates incorporates covariates proportionally, with the residual distribution determined from a smooth non-parametric state-dependent form. Computation of the resulting probabilities is discussed, leading to model estimation using a penalized likelihood function. Two data sets are used as illustrative examples, one representing underdispersed Poisson-like data and the other overdispersed binomial-like data.
| Item Type: | Journal Article |
|---|---|
| RM Number: | 2005001103 |
| Status: | Published |
| Keywords: | count data; over and underdispersion; covariate effects; extended Poisson process model; penalized likelihood |
| Subjects: | 230000 Mathematical Sciences > 230200 Statistics > 230204 Applied Statistics |
| ID Code: | 8172 |
| Deposited By: | Conlon, Kylie |
| Deposited On: | 21 June 2007 |
| Alternative Locations: | http://dx.doi.org/10.1023/B:STCO.0000039480.66002.5a |
| Copyright Owner: | Copyright 2004 Springer |
| Copyright Statement: | The original publication is available at SpringerLink http://www.springerlink.com |
| Additional Information: | For more information, please refer to the journal's website (see hypertext link) or contact the author. Author contact details: m.faddy@qut.edu.au |