Robust inference in the negative binomial regression model with an application to falls data

DOI10.1111/biom.12212zbMath1393.62011OpenAlexW1919258739WikidataQ30844859 ScholiaQ30844859MaRDI QIDQ3465370

William H. Aeberhard, Eva Cantoni, Stephane Heritier

Publication date: 21 January 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/biom.12212

zbMATH Keywords

generalized linear modelsnegative binomial regressionweighted maximum likelihoodbounded influence functionoverdispersed count dataredescending estimatorsrobust \(M\)-estimators

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Robustness and adaptive procedures (parametric inference) (62F35)

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Robust inference in the multilevel zero-inflated negative binomial model ⋮ On robust estimation of negative binomial INARCH models ⋮ Robust estimation in generalized linear models: the density power divergence approach ⋮ Minimum density power divergence estimator for negative binomial integer-valued GARCH models ⋮ Saddlepoint tests for accurate and robust inference on overdispersed count data ⋮ Quantile regression for overdispersed count data: a hierarchical method ⋮ Robust Inference and Modeling of Mean and Dispersion for Generalized Linear Models ⋮ Consistency of \(\ell_1\) penalized negative binomial regressions ⋮ A robust conditional maximum likelihood estimator for generalized linear models with a dispersion parameter ⋮ Weak linear representation of M-estimaton in GLMs with dependent errors ⋮ Robust Wald-type tests in GLM with random design based on minimum density power divergence estimators ⋮ Robust quasi-likelihood estimation for the negative binomial integer-valued GARCH(1,1) model with an application to transaction counts

Uses Software

• R
• COUNT

Cites Work

• Unnamed Item
• Unnamed Item
• Implementing the Bianco and Yohai estimator for logistic regression
• Robust tests in generalized linear models with missing responses
• Resistant estimators in Poisson and gamma models with missing responses and an application to outlier detection
• Properties of robust m-estimators for poisson and negative binomial data^∗
• Negative Binomial Regression
• Estimation of the Negative Binomial Parameter κ by Maximum Quasi -Likelihood
• Negative binomial and mixed poisson regression
• Robust Inference for Generalized Linear Models
• Robust Statistics

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