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New mixture distributions for modelling count data

Rose Baker

Statistical Modelling2025https://doi.org/10.1177/1471082x251357353article
ABDC B
Weight
0.37

What the paper says

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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https://doi.org/https://doi.org/10.1177/1471082x251357353

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@article{rose2025,
  title        = {{New mixture distributions for modelling count data}},
  author       = {Rose Baker},
  journal      = {Statistical Modelling},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/1471082x251357353},
}

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New mixture distributions for modelling count data

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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