Minimum density power divergence estimator for covariance matrix based on skew t distribution

被引：0

作者：

Kim, Byungsoo ^{[1
]}

Lee, Sangyeol ^{[2
]}

机构：

[1] Yeungnam Univ, Dept Stat, Kyungsan 712749, South Korea

[2] Seoul Natl Univ, Dept Stat, Seoul 151747, South Korea

来源：

STATISTICAL METHODS AND APPLICATIONS | 2014年 / 23卷 / 04期

基金：

新加坡国家研究基金会;

关键词：

Minimum density power divergence; Robust estimation; Covariance matrix; Skew t distribution; ROBUST ESTIMATION; MULTIVARIATE; LOCATION;

D O I：

10.1007/s10260-014-0284-5

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper, we study the problem of estimating the covariance matrix of stationary multivariate time series based on the minimum density power divergence method that uses a multivariate skew t distribution family. It is shown that under regularity conditions, the proposed estimator is strongly consistent and asymptotically normal. A simulation study is provided for illustration.

引用

页码：565 / 575

页数：11

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