The robust estimation method for a finite mixture of Poisson mixed-effect models

DOI10.1016/J.CSDA.2011.12.006zbMath1243.62044OpenAlexW1983292423MaRDI QIDQ434997

Andy H. Lee, Liming Xiang, Kelvin. K. W. Yau

Publication date: 16 July 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.12.006

zbMATH Keywords

robustnessnonparametric maximum likelihoodminimum Hellinger distance

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric robustness (62G35) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Related Items (3)

Using AVK method to solve nonlinear problems with uncertain parameters ⋮ A mixture model-based nonparametric approach to estimating a count distribution ⋮ Special issue on robust analysis of complex data

Cites Work

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• A data-based method for selecting tuning parameters in minimum distance estimators
• Robust estimation of mixture complexity for count data
• Minimum Hellinger Distance Estimation for Finite Mixtures of Poisson Regression Models and Its Applications
• Minimum Hellinger Distance Estimation for k-Component Poisson Mixture with Random Effects
• Statistical analysis of finite mixture distributions
• Finite mixture models
• A General Maximum Likelihood Analysis of Variance Components in Generalized Linear Models

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