Robust adaptive estimators for binary regression models

DOI10.1016/j.jspi.2004.02.006zbMath1061.62036OpenAlexW2065464990WikidataQ58194148 ScholiaQ58194148MaRDI QIDQ1772675

Daniel Gervini

Publication date: 21 April 2005

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2004.02.006

zbMATH Keywords

tablesWeighted maximum likelihoodLogistic regressionRobust confidence intervalsEfficient estimation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Parametric tolerance and confidence regions (62F25) Generalized linear models (logistic models) (62J12) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (8)

Robust variable selection in the logistic regression model ⋮ Regularized robust estimation in binary regression models ⋮ Robust estimation for ordinal regression ⋮ Robust median estimator in logistic regression ⋮ Robust Wald-type methods for testing equality between two populations regression parameters: a comparative study under the logistic model ⋮ Unnamed Item ⋮ Unnamed Item ⋮ Robust link functions

Cites Work

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• A note on A. Albert and J. A. Anderson's conditions for the existence of maximum likelihood estimates in logistic regression models
• Least-absolute-deviations fits for generalized linear models
• Asymptotic Statistics
• Conditionally Unbiased Bounded-Influence Estimation in General Regression Models, with Applications to Generalized Linear Models
• Robust estimation in the logistic regression model

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