New mixture distributions for modelling count data

A class of new 1-parameter underdispersed distributions is introduced. Mixed with Poisson distributions; they generate 2- and 3-parameter discrete distributions that generalize the Poisson distribution and can be both under and over-dispersed. Probabilities are easy to compute and moments and random number generation are tractable. The distributions are described, and they are fitted to some underdispersed and overdispersed datasets. We show how inference for the effect of covariates sharpens on moving from the Poisson model. The fits compare favourably to two benchmarks, the COM Poisson distribution and the weighted Poisson distribution.

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Publication Details

Journal
Statistical Modelling
Published
2025-07-25
DOI
https://doi.org/10.1177/1471082x251357353
Citations
1
Primary Topic
Bayesian Methods and Mixture Models
Type
article
Field-Weighted Citation Impact
2.48
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article

New mixture distributions for modelling count data

Rose Baker
1 citations
Statistical Modelling
Bayesian Methods and Mixture Models
2.48
article

New mixture distributions for modelling count data

Rose Baker
article en
1 citations

Abstract

A class of new 1-parameter underdispersed distributions is introduced. Mixed with Poisson distributions; they generate 2- and 3-parameter discrete distributions that generalize the Poisson distribution and can be both under and over-dispersed. Probabilities are easy to compute and moments and random number generation are tractable. The distributions are described, and they are fitted to some underdispersed and overdispersed datasets. We show how inference for the effect of covariates sharpens on moving from the Poisson model. The fits compare favourably to two benchmarks, the COM Poisson distribution and the weighted Poisson distribution.

Statistical Modelling
University of Salford (GB)
Openalex Percentile: Top 9%
Bayesian Methods and Mixture Models
2.48
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