A model-free test for reduced rank in multivariate regression

被引：49

作者：

Cook, RD ^{[1
]}

Setodji, CM

机构：

[1] Univ Minnesota, Sch Stat, St Paul, MN 55108 USA

[2] RAND Corp, Santa Monica, CA 90407 USA

来源：

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 2003年 / 98卷 / 462期

关键词：

central subspaces; dimension reduction; multivariate regression; regression; regression graphics;

D O I：

10.1198/016214503000134

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 propose a test of dimension in multivariate regression. This test is in the spirit of tests on the rank of the coefficient matrix in a multivariate linear model, but it does not require a prespecified model. The test may be particularly useful at the outset of an analysis before a multivariate model is posited, because it can lead to low-dimensional summary plots that are inferred to contain all of the sample information on the multivariate mean function.

引用

页码：340 / 351

页数：12

共 27 条

[1] ESTIMATING LINEAR RESTRICTIONS ON REGRESSION COEFFICIENTS FOR MULTIVARIATE NORMAL DISTRIBUTIONS [J].