On the existence of maximum likelihood estimators in Poisson-gamma HGLM and negative binomial regression model

DOI10.1214/13-EJS852zbMath1293.62142OpenAlexW2064443965MaRDI QIDQ375217

Lucien Diégane Gning, Daniel Pierre-Loti-Viaud

Publication date: 29 October 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1381759272

zbMATH Keywords

count datarandom effectshierarchical generalized linear modelnegative binomial regressionPoisson-gamma HGLM

Mathematics Subject Classification ID

Point estimation (62F10) General nonlinear regression (62J02)

Related Items

Note on the singularity of the Poisson-gamma model ⋮ Hierarchical generalized linear models, correlation and a posteriori ratemaking

Uses Software

• HGLMMM
• GWRM

Cites Work

• Longitudinal data analysis using generalized linear models
• On maximum likelihood estimates in multiplicative Poisson and negative binomial models
• A generalized Waring regression model for count data
• Compound multinomial likelihood functions are unimodal: Proof of a conjecture of I. J. Good
• Log-linear models for frequency data: sufficient statistics and likelihood equations
• Models for Longitudinal Data: A Generalized Estimating Equation Approach
• On the Effect of the Number of Quadrature Points in a Logistic Random Effects Model: An Example
• Small-sample estimation of negative binomial dispersion, with applications to SAGE data
• Negative Binomial Regression
• Generalized Linear Models with Random Effects
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