Mean and Variance for Count Regression Models Based on Reparameterized Distributions

DOI10.1007/S13571-024-00325-ZMaRDI QIDQ6494003

Célestin C. Kokonendji, Marcelo Bourguignon, Rodrigo M. R. de Medeiros

Publication date: 29 April 2024

Published in: Sankhyā. Series B (Search for Journal in Brave)

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) Characterization and structure theory of statistical distributions (62E10)

Cites Work

• A flexible zero-inflated model to address data dispersion
• Log-symmetric distributions: statistical properties and parameter estimation
• A regression model for overdispersed data without too many zeros
• A simple and useful regression model for fitting count data
• On the mean-parameterized Bell-Touchard regression model for count data
• A simple and useful regression model for underdispersed count data based on Bernoulli-Poisson convolution
• On Poisson-exponential-Tweedie models for ultra-overdispersed count data
• The analysis of zero-inflated count data: Beyond zero-inflated Poisson regression.
• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
• Zero‐Inflated Poisson and Binomial Regression with Random Effects: A Case Study
• On some aspects of a zero-inflated overdispersed model and its applications
• On the two-parameter Bell–Touchard discrete distribution
• Generalized Poisson Distribution: the Property of Mixture of Poisson and Comparison with Negative Binomial Distribution
• Univariate Discrete Distributions
• Count Data Distributions
• A Class of Random Variables with Discrete Distributions
• EXPERIMENTAL EVIDENCE CONCERNING CONTAGIOUS DISTRIBUTIONS IN ECOLOGY
• Visualizing Count Data Regressions Using Rootograms
• A generalization to zero-inflated hyper-Poisson distribution: Properties and applications

This page was built for publication: Mean and Variance for Count Regression Models Based on Reparameterized Distributions