Bayesian Conway–Maxwell–Poisson regression models for overdispersed and underdispersed counts

DOI10.1080/03610926.2019.1682162OpenAlexW2980208522MaRDI QIDQ5078524

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Publication date: 23 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1910.06008

zbMATH Keywords

count dataoverdispersionunderdispersionBayesian generalized linear modelConway-Maxwell-Poisson

Mathematics Subject Classification ID

Bayesian inference (62F15) Statistics (62-XX)

Related Items (1)

Uniformly most powerful unbiased tests for the dispersion parameter of the Conway-Maxwell-Poisson distribution

Uses Software

• Mcmcpack
• BRugs
• mpcmp

Cites Work

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• A hyper-Poisson regression model for overdispersed and underdispersed count data
• A flexible regression model for count data
• Generalized poisson regression model
• Efficient Bayesian inference for COM-Poisson regression models
• A First Course in Bayesian Statistical Methods
• Underdispersion models: Models that are “under the radar”
• Mean-parametrized Conway–Maxwell–Poisson regression models for dispersed counts
• Extended Poisson–Tweedie: Properties and regression models for count data
• A Useful Distribution for Fitting Discrete Data: Revival of the Conway–Maxwell–Poisson Distribution
• Conjugate analysis of the Conway-Maxwell-Poisson distribution

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