A new family of BAN estimators for polytomous logistic regression models based on \(\varphi\)-diver\-gence measures

DOI10.1007/s10260-006-0008-6zbMath1157.62415OpenAlexW2140869134MaRDI QIDQ1001725

Arjun K. Gupta, Truc T. Nguyen, Leandro Pardo, Dhanuja Kasturiratna

Publication date: 24 February 2009

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-006-0008-6

zbMATH Keywords

Kullback-Leibler divergence measuremultinomial samplingminimum \(\varphi\)-divergence estimatorpolytomous regression model

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12) General nonlinear regression (62J02) Contingency tables (62H17)

Related Items (6)

Variable selection via penalized minimum φ-divergence estimation in logistic regression ⋮ Phi-divergences and polytomous logistic regression models: An overview ⋮ Robust semiparametric inference for polytomous logistic regression with complex survey design ⋮ An extension of likelihood-ratio-test for testing linear hypotheses in the baseline-category logit model ⋮ Residuals for polytomous logistic regression models based on φ-divergences test statistics ⋮ Minimum phi-divergence estimators for multinomial logistic regression with complex sample design

Uses Software

• DiVer

Cites Work

• Polytomous logistic regression
• Multiple-Group Logistic Regression Diagnostics
• Multiple group logistic discrimination
• Separate sample logistic discrimination
• Linear Statistical Inference and its Applications
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