Improved estimation of kurtosis parameters for two multivariate populations

被引：1

作者：

Zahra N. ^{[1
]}

Lisawadi S. ^{[1
]}

Ahmed S.E. ^{[2
]}

机构：

[1] Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Bangkok

[2] Department of Mathematics and Statistics, Brock University, St. Catharines, ON

来源：

Lobachevskii Journal of Mathematics | 2017年 / 38卷 / 1期

关键词：

asymptotic distributional bias; asymptotic quadratic risk; kurtosis; preliminary test; shrinkage; uncertain prior information;

D O I：

10.1134/S1995080217010218

中图分类号：

学科分类号：

摘要：

Improved estimators for the kurtosis parameters of two multivariate populations are developed under the assumption that they are equal. Shrinkage and preliminary test estimators are proposed and their asymptotic properties are presented analytically and numerically. Comparisons of the suggested estimators are made on the basis of their asymptotic distributional biases and asymptotic quadratic risks. It is observed that the suggested estimators perform better than the estimator based on the sample data only in a wider range of parametric space. © 2017, Pleiades Publishing, Ltd.

引用

页码：110 / 115

页数：5

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