Comparison of Risk Ratios of Shrinkage Estimators in High Dimensions

Autor:	Abdenour Hamdaoui, Waleed Almutiry, Mekki Terbeche, Abdelkader Benkhaled
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	balanced loss function James–Stein estimator multivariate normal distribution noncentral chi-square distribution positive-part version of James–Stein estimator shrinkage estimators Mathematics QA1-939
Zdroj:	Mathematics, Vol 10, Iss 1, p 52 (2021)
Druh dokumentu:	article
ISSN:	2227-7390
DOI:	10.3390/math10010052
Popis:	In this paper, we analyze the risk ratios of several shrinkage estimators using a balanced loss function. The James–Stein estimator is one of a group of shrinkage estimators that has been proposed in the existing literature. For these estimators, sufficient criteria for minimaxity have been established, and the James–Stein estimator’s minimaxity has been derived. We demonstrate that the James–Stein estimator’s minimaxity is still valid even when the parameter space has infinite dimension. It is shown that the positive-part version of the James–Stein estimator is substantially superior to the James–Stein estimator, and we address the asymptotic behavior of their risk ratios to the maximum likelihood estimator (MLE) when the dimensions of the parameter space are infinite. Finally, a simulation study is carried out to verify the performance evaluation of the considered estimators.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/56c9b1a9e872419d998acd2052a62e30 Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
Nepřihlášeným uživatelům se plný text nezobrazuje	K zobrazení výsledku je třeba se přihlásit.