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Unified predictor hypothesis tests in sufficient dimension reduction: A bootstrap approach

Title
Unified predictor hypothesis tests in sufficient dimension reduction: A bootstrap approach
Authors
Yoo J.K.
Ewha Authors
유재근
SCOPUS Author ID
유재근scopus
Issue Date
2011
Journal Title
Journal of the Korean Statistical Society
ISSN
1226-3192JCR Link
Citation
vol. 40, no. 2, pp. 217 - 225
Indexed
SCIE; SCOPUS; KCI WOS scopus
Abstract
In this paper, we newly define a unified predictor hypothesis that is applicable to all sufficient dimension reduction (SDR) methodologies. To test the predictor hypothesis, we propose a bootstrap approach by measuring the distances between reference subspaces and bootstrap subspaces. To measure the distances between two subspaces, the vector correlation coefficient is considered. Simulation studies confirm the background reasoning of the proposed tests. © 2010 The Korean Statistical Society.
DOI
10.1016/j.jkss.2010.09.006
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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