论文|Junhao Guo, Jie Zhou and Sanfeng Hu. Intrinsic Covariance Matrix Estimation for Multivariate Elliptical Distributions

本文原载Statistics & Probability Letters，由四川大学数学学院周杰教授等科研人员创作，系四川大学“智慧法治”超前部署学科系列学术成果。后续会持续分享四川大学“智慧法治”超前部署学科系列学术成果，欢迎大家阅读。

Abstract: The property of statistical models not depending on the coordinate systems or model parametrization is one main interest of intrinsic inference in statistics. The intrinsic covariance matrix estimation is addressed for multivariate elliptical distributions in this paper. An optimal intrinsic covariance estimator is derived in the sense of minimizing the mean square Rao distance, and proved to own intrinsic unbiasedness. Specifically, the intrinsically unbiased estimators for elliptical distributions and mixture elliptical distributions are developed.

Keywords: Rao distance; Elliptical distributions; Covariance matrix estimation; Intrinsically unbiased estimation; Mixture of multivariate elliptical distributions

Junhao Guo, Jie Zhou and Sanfeng Hu. Intrinsic Covariance Matrix Estimation for Multivariate Elliptical Distributions, Statistics and Probability Letters, Vol. 162, Article 108774, July 2020.（论文下载）