Pre-Test type estimators for selection of simple normal models

DOI10.1080/00949659408811619zbMath0838.62044OpenAlexW1983936337MaRDI QIDQ4869573

J. H. Venter, S. J. Steel

Publication date: 26 March 1996

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

Full work available at URL: https://doi.org/10.1080/00949659408811619

zbMATH Keywords

Stein estimationsquared errorrisk estimatorcomplexity cost lossregression principal componentssome zeros family

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12)

Related Items (1)

Variable selection and error rate estimation in discriminant analysis

Cites Work

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• Improved estimation under collinearity and squared error loss
• Parametric robustness: Small biases can be worthwhile
• An adaptive empirical Bayes estimator of the multivariate normal mean under quadratic loss
• Estimating the mean of a normal distribution with loss equal to squared error plus complexity cost
• On the inadmissibility of preliminary-test estimators when the loss involves a complexity cost
• Maximum likelihood estimation of a compound Poisson process
• The extended Stein procedure for simultaneous model selection and parameter estimation
• Some comments on estimation in regression after preliminary tests of significance
• The Admissibility of a Preliminary Test Estimator When the Loss Incorporates a Complexity Cost
• The Little Bootstrap and Other Methods for Dimensionality Selection in Regression: X-Fixed Prediction Error
• Numerical Specification of Discrete Least Favorable Prior Distributions
• Simultaneous selection and estimation for the some zeros family of normal models
• Non-Optimality of Preliminary-Test Estimators for the Mean of a Multivariate Normal Distribution
• Estimating the probability of correct selection

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