A new confidence interval for all characteristic roots of a covariance matrix

被引：0

作者：

Fumitake Sakaori

Takayuki Yamada

Akihisa Kawamura

Takakazu Sugiyama

机构：

[1] Rikkyo University,College of Sociology

[2] Chuo University,Department of Mathematics

来源：

Computational Statistics | 2007年 / 22卷

关键词：

Characteristic root; Confidence interval; Perturbation expansion;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Confidence intervals for all of the characteristic roots of a sample covariance matrix are derived. Using a perturbation expansion, we obtain a new confidence interval for these roots. Then, we propose another confidence interval based on the results of Monte Carlo simulations. Since it is based on simulations, this new confidence interval is both narrower and more accurate than others when the difference between the largest and smallest characteristic roots of the population covariance matrix is large.

引用

页码：121 / 131

页数：10

共 6 条

[1] Anderson GA(1965)An asymptotic expansion for the distribution of the latent roots of the estimated covariance matrix Ann Math Stat 36 1153-1173
[2] James AT(1960)The distribution of the latent roots of the covariance matrix Ann Math Stat 31 151-158
[3] Konishi S(1977)Asymptotic expansion for the distribution of a function of latent roots of the covariance matrix Ann Inst Stat Math 29 389-396
[4] Konishi S(1981)Improved approximations to distributions of the largest and the smallest latent roots of a Wishart matrix Ann Inst Stat Math 33 27-33
[5] Sugiyama T(1970)Joint distribution of the extreme roots of a covariance matrix Ann Math Stat 41 655-657
[6] Sugiyama T(undefined)undefined undefined undefined undefined-undefined

← 1 →