Latent variable analysis and partial correlation graphs for multivariate time series

被引：6

作者：

Fried, R ^{[1
]}

Didelez, V

机构：

[1] Univ Carlos III Madrid, Dept Estad, E-28903 Getafe, Spain

[2] UCL, London WC1E 6BT, England

来源：

STATISTICS & PROBABILITY LETTERS | 2005年 / 73卷 / 03期

关键词：

time series analysis; dimension reduction; factor analysis; partial correlations;

D O I：

10.1016/j.spl.2005.04.002

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：

We investigate the possibility of exploiting partial correlation graphs for identifying interpretable latent variables underlying a multivariate time series. It is shown how the collapsibility and separation properties of partial correlation graphs can be used to understand the relation between a factor model and the structure among the observable variables. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：287 / 296

页数：10

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