Robust semiparametric inference for polytomous logistic regression with complex survey design

DOI10.1007/s11634-020-00430-7OpenAlexW3109627129MaRDI QIDQ2051581

Abhik Ghosh, Elena Castilla, Nirian Martín, Leandro Pardo

Publication date: 24 November 2021

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1904.02219

zbMATH Keywords

robustnessquasi-likelihooddesign effectcluster samplingpolytomous logistic regression modelminimum quasi weighted DPD estimatorpseudo minimum phi-divergence estimator

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Hypothesis testing in multivariate analysis (62H15) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35)

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Cites Work

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• Robust estimation for independent non-homogeneous observations using density power divergence with applications to linear regression
• New improved estimators for overdispersion in models with clustered multinomial data and unequal cluster sizes
• Robust Wald-type tests for non-homogeneous observations based on the minimum density power divergence estimator
• Robustness against separation and outliers in logistic regression
• Implementing the Bianco and Yohai estimator for logistic regression
• Robust testing in the logistic regression model
• A new family of BAN estimators for polytomous logistic regression models based on \(\varphi\)-diver\-gence measures
• Minimum Hellinger distance estimates for parametric models
• Efficiency versus robustness: The case for minimum Hellinger distance and related methods
• On robustness and efficiency of minimum divergence estimators
• Minimum phi-divergence estimators for multinomial logistic regression with complex sample design
• A Wald-type test statistic for testing linear hypothesis in logistic regression models based on minimum density power divergence estimator
• Minimum Hellinger distance estimators for some multivariate models: influence functions and breakdown point results
• A characteristic function approach to the biased sampling model, with application to robust logistic regression
• Robust estimation in generalized linear models: the density power divergence approach
• Logistic regression analysis of sample survey data
• On the Variances of Asymptotically Normal Estimators from Complex Surveys
• Residuals for polytomous logistic regression models based on φ-divergences test statistics
• Multiple-Group Logistic Regression Diagnostics
• Outlier Robust Finite Population Estimation
• Robust and efficient estimation by minimising a density power divergence
• A One-Step Gauss-Newton Estimator for Modelling Categorical Data with Extraneous Variation
• Robust estimation for non-homogeneous data and the selection of the optimal tuning parameter: the density power divergence approach
• Choosing a robustness tuning parameter
• A unified approach to robust estimation in finite population sampling
• Statistical Inference

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