A study of minimax shrinkage estimators dominating the James-Stein estimator under the balanced loss function

A study of minimax shrinkage estimators dominating the James-Stein estimator under the balanced loss function

One of the most common challenges in multivariate statistical analysis is estimating the mean parameters. A well-known approach of estimating the mean parameters is the maximum likelihood estimator (MLE). However, the MLE becomes inefficient in the case of having large-dimensional parameter space. A...

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Bibliographic Details
Main Authors: Benkhaled Abdelkader, Hamdaoui Abdenour, Almutiry Waleed, Alshahrani Mohammed, Terbeche Mekki
Format: Article
Language:English
Published: De Gruyter 2022-02-01
Series:Open Mathematics
Subjects:
balanced loss function
james-stein estimator
multivariate normal distribution
non-central chi-square distribution
shrinkage estimators
62j07
62c20
62h10
Online Access:https://doi.org/10.1515/math-2022-0008

Internet

https://doi.org/10.1515/math-2022-0008

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