On Minimaxity and Limit of Risks Ratio of James-Stein Estimator Under the Balanced Loss Function

DOI10.46793/kgjmat2303.459hOpenAlexW4379881816MaRDI QIDQ6166522

Abdelkader Benkhaled, Abdenour Hamdaoui, Mekki Terbeche

Publication date: 2 August 2023

Published in: Kragujevac Journal of Mathematics (Search for Journal in Brave)

Full work available at URL: http://elib.mi.sanu.ac.rs/files/journals/kjm/77/kjmn77p459-479.pdf

zbMATH Keywords

James-Stein estimatorshrinkage estimatorminimaxitynon-central chi-square distributionbalanced loss functionrisk ratiomultivariate Gaussian random variable

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Minimax procedures in statistical decision theory (62C20)

Related Items (1)

Limits of Risks Ratios of Shrinkage Estimators under the Balanced Loss Function

Cites Work

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• Optimal shrinkage estimation of mean parameters in family of distributions with quadratic variance
• Estimating the mean function of a Gaussian process and the Stein effect
• Estimation of the mean of a multivariate normal distribution
• Minimax estimators of the mean of a multivariate normal distribution
• Admissible minimax estimation of a multivariate normal mean with arbitrary quadratic loss
• The optimal extended balanced loss function estimators
• Estimation of a normal mean relative to balanced loss functions
• Asymptotic properties of risks ratios of shrinkage estimators
• Limit expressions for the risk of james‐stein estimators
• Generalized james-stein estimatoes
• More on the restricted ridge regression estimation
• Estimating the Mean of a Multivariate Normal Population with General Quadratic Loss Function
• The Risk of James–Stein and Lasso Shrinkage

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