 A link-free approach for testing common indices for three or more multi-index modelsXuejing Liu, Lei Huo, Xuerong Meggie Wen and Robert Paige Journal of Multivariate Analysis, 2017, vol. 153, issue C, 236-245 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. Keywords: Sufficient dimension reduction; Multiple populations; Common principal component analysis; Multi-index model (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:153:y:2017:i:c:p:236-245 Ordering information: This journal article can be ordered from DOI: 10.1016/j.jmva.2016.10.002 Access Statistics for this article Journal of Multivariate Analysis is currently edited by de Leeuw, J. More articles in Journal of Multivariate Analysis from Elsevier |
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