On Some Classes of Estimators Derived from the Positive Part of James–Stein Estimator. (8th April 2023)

• Record Type: Journal Article
• Authors: Hamdaoui, Abdenour; Benkhaled, Abdelkader; Alshahrani, Mohammed; Terbeche, Mekki; Almutiry, Waleed; Alahmadi, Amani
• Other Names: Jan Naeem Academic Editor.
• Is Part Of: Journal of mathematics. Volume 2023(2023)
• Publication Date: 2023-04-08
• Subjects: Mathematics -- Periodicals; Mathematics; Periodicals; 510
• DOI: 10.1155/2023/5221061
• Languages: English
• ISSNs: 2314-4629

Abstract

Abstract : This work consists of developing shrinkage estimation strategies for the multivariate normal mean when the covariance matrix is diagonal and known. The domination of the positive part of James–Stein estimator (PPJSE) over James–Stein estimator (JSE) relative to the balanced loss function (BLF) is analytically proved. We introduce a new class of shrinkage estimators which ameliorate the PPJSE, and then we construct a series of polynomial shrinkage estimators which improve the PPJSE; also, any estimator of this series can be ameliorated by adding to it a new term of higher degree. We end this paper by simulation studies which confirm the performance of the suggested estimators.