[1]李小雪,明瑞星.高维协方差矩阵估计方法的比较[J].江西师范大学学报(自然科学版),2015,(06):599-604.
 LI Xiaoxue,MING Ruixing.The Comparison of Methods for Estimating the High-Dimensional Covariance Matrices[J].,2015,(06):599-604.
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高维协方差矩阵估计方法的比较()
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《江西师范大学学报》(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2015年06期
页码:
599-604
栏目:
出版日期:
2015-12-31

文章信息/Info

Title:
The Comparison of Methods for Estimating the High-Dimensional Covariance Matrices
作者:
李小雪;明瑞星
浙江工商大学统计与数学学院,浙江 杭州 310018
Author(s):
LI XiaoxueMING Ruixing
School of Statistics and Mathematics,Zhejiang Gongshang University,Hangzhou Zhejiang 310018,China
关键词:
高维协方差矩阵 稀疏矩阵 非稀疏矩阵 门限估计 收缩估计
Keywords:
high-dimensional covariance matrix sparse matrix non-parse matrix thresholding estimation shrinkage estimation
分类号:
F 224
文献标志码:
A
摘要:
通过模拟比较门限估计方法和收缩估计方法之间的差异,得出2种方法在实际应用中的使用范围.由模拟结果可知,若有确切的证据表明总体协方差矩阵是稀疏矩阵,则采用门限估计方法,否则,采用稳健的收缩估计方法比较恰当.
Abstract:
The differences between the thresholding estimation and the shrinking estimation are reported by a series of simulations,and the proper estimation is proposed within these two estimations in practice.The simulations show that if the population covariance matrix is a sparse matrix,the thresholding estimation is better than that of the shrinking estimation,and vice versa.

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备注/Memo

备注/Memo:
基金项目:浙江省高校人文社科重点研究基地(统计学),浙江省自然科学基金(LY16A01001)和浙江省教育厅课题(1020KZ0413455)资助项目.
更新日期/Last Update: 1900-01-01