Model selection and parameter estimation of a multinomial logistic regression model

DOI10.1080/00949655.2012.746347zbMath1453.62595OpenAlexW2048837274MaRDI QIDQ5219998

Shakhawat Hossain, Hatem A. Howlader, S. Ejaz Ahmed

Publication date: 9 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2012.746347

zbMATH Keywords

likelihood ratio testMonte Carlo simulationshrinkage estimatorsmultinomial logistic regressionLassoasymptotic distributional bias and risk

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Generalized linear models (logistic models) (62J12)

Uses Software

• glmnet
• ElemStatLearn

Cites Work

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• SHRINKAGE, PRETEST AND ABSOLUTE PENALTY ESTIMATORS IN PARTIALLY LINEAR MODELS
• The Group Lasso for Logistic Regression
• Local Asymptotic Specification Error Analysis
• On the asymptotic normality of multinomial population size estimators with application to backcalculation of AIDS epidemic
• Asymptotic Statistics
• L 1-Regularization Path Algorithm for Generalized Linear Models
• A Semiparametric Basis for Combining Estimation Problems Under Quadratic Loss

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