A Link-Free Approach for Testing Common Indices for Three or More Multi-Index Models

Abstract

Liu et al. (2015) proposed a novel link-free procedure for testing whether two multi-index models share identical indices via the sufficient dimension reduction approach. However, their method can only be applied to data with two populations. In practice, we often deal with situations where the same variables are being measured on objects from three or more groups, and we would like to know how similar these groups are with respect to some overall features. In this paper, we propose a link-free method which could test if three or more multi-index models share the same indices. The asymptotic properties of our test statistic are developed. Numerical studies and a real data analysis are conducted to illustrate the performance of our method.

Department(s)

Mathematics and Statistics

Keywords and Phrases

Common principal component analysis; Multi-index model; Multiple populations; Sufficient dimension reduction

International Standard Serial Number (ISSN)

0047-259X

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2017 Elsevier, All rights reserved.

Publication Date

01 Jan 2017

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