Stein-type estimation in logistic regression models based on minimum \(\phi\)-divergence estimators
DOI10.1016/j.jkss.2008.07.003zbMath1293.62051OpenAlexW2014923380MaRDI QIDQ2510609
Leandro Pardo, M. Luisa Menendez, María del Carmen Pardo
Publication date: 1 August 2014
Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jkss.2008.07.003
logistic regression modelminimum phi-divergence estimatorphi-divergence test statisticsgeneral linear hypothesesStein-type estimation
Asymptotic properties of parametric estimators (62F12) Point estimation (62F10) Parametric inference under constraints (62F30) Analysis of variance and covariance (ANOVA) (62J10)
Cites Work
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- Construction of improved estimators in multiparameter estimation for discrete exponential families
- Minimum \(\phi\)-divergence estimator in logistic regression models
- Preliminary test estimators and phi-divergence measures in generalized linear models with binary data
- Statistical decision theory and Bayesian analysis. 2nd ed
- Theory of statistical inference and information. Transl. from the Slovak by the author
- Stein estimation -- a review
- The analysis of ordered categorical data: An overview and a survey of recent developments. (With discussion)
- Testing in logistic regression models based on \(\phi\)-divergences measures
- A Family of Minimax Estimators of the Mean of a Multivariate Normal Distribution
- Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
- Phi-Divergence Statistics for Testing Linear Hypotheses in Logistic Regression Models
- Theory of Preliminary Test and Stein‐Type Estimation With Applications
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