On robustness of maximum likelihood estimates for Poisson-lognormal models.

DOI10.1016/J.SPL.2003.11.003zbMath1104.62081OpenAlexW1982653426MaRDI QIDQ1423035

Paul J. Smith, Kimberly S. Weems

Publication date: 14 February 2004

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2003.11.003

zbMATH Keywords

Maximum likelihood estimationderivativesRobustnessGâteauxGeneralized linear mixed modelsInfluence functions

Mathematics Subject Classification ID

Point estimation (62F10) Generalized linear models (logistic models) (62J12) Robustness and adaptive procedures (parametric inference) (62F35) Diagnostics, and linear inference and regression (62J20)

Related Items (1)

Discriminant analysis with mixed non normal variables

Cites Work

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• Negative binomial and mixed poisson regression
• Nonlinear Regression on Cross-Section Data
• Analysis of Overdispersed Count Data by Mixtures of Poisson Variables and Poisson Processes
• LOG‐LINEAR MODELS FOR MEAN AND DISPERSION IN MIXED POISSON REGRESSION MODELS
• The effect of mixing‐distribution misspecification in conjugate mixture models
• Robust Statistics

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