Robust Inference and Modeling of Mean and Dispersion for Generalized Linear Models

DOI10.1080/01621459.2022.2140054MaRDI QIDQ6154023

Stefan Van Aelst, Pieter Segaert, Unnamed Author, Tim Verdonck

Publication date: 19 March 2024

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

zbMATH Keywords

likelihood ratio testpenalizationinfluence function\(M\)-estimatordouble exponential family

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• The Adaptive Lasso and Its Oracle Properties
• Joint estimation and variable selection for mean and dispersion in proper dispersion models
• Robust estimators for generalized linear models
• Robust joint modeling of mean and dispersion through trimming
• Robust binary regression
• On the relation between S-estimators and M-estimators of multivariate location and covariance
• Adaptive variance function estimation in heteroscedastic nonparametric regression
• Implementing the Bianco and Yohai estimator for logistic regression
• Nonsmooth analysis and Fréchet differentiability of M-functionals
• Saddlepoint tests for accurate and robust inference on overdispersed count data
• On the uniqueness of \(S\)-functionals and \(M\)-functionals under nonelliptical distributions.
• Fast robust estimation of prediction error based on resampling
• A characteristic function approach to the biased sampling model, with application to robust logistic regression
• High-dimensional graphs and variable selection with the Lasso
• Robust estimation in generalized linear models: the density power divergence approach
• Robust Estimation of Mean and Dispersion Functions in Extended Generalized Additive Models
• Projection Estimators for Generalized Linear Models
• An Outlier-Robust Fit for Generalized Additive Models With Applications to Disease Outbreak Detection
• Least Median of Squares Regression
• Robust inference in the negative binomial regression model with an application to falls data
• Minimum distance estimation for the logistic regression model
• Double Exponential Families and Their Use in Generalized Linear Regression
• An extended quasi-likelihood function
• Variance Function Estimation
• Algorithm AS 155: The Distribution of a Linear Combination of χ 2 Random Variables
• Least-absolute-deviations fits for generalized linear models
• Robust Bounded-Influence Tests in General Parametric Models
• Generalized linear models for the analysis of quality-improvement experiments
• Numerical Methods for Nonlinear Estimating Equations
• Robust Inference for Generalized Linear Models
• Conditionally Unbiased Bounded-Influence Estimation in General Regression Models, with Applications to Generalized Linear Models
• Robust variable screening for regression using factor profiling
• Variance Function Partially Linear Single-Index Models
• Robust and consistent variable selection in high-dimensional generalized linear models
• Robust estimation for linear regression with asymmetric errors
• Robust Statistics
• Robust inference with GMM estimators

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