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

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DC Field	Value	Language
dc.contributor.author	유재근	*
dc.date.accessioned	2016-08-28T12:08:44Z	-
dc.date.available	2016-08-28T12:08:44Z	-
dc.date.issued	2011	*
dc.identifier.issn	1226-3192	*
dc.identifier.other	OAK-7628	*
dc.identifier.uri	https://dspace.ewha.ac.kr/handle/2015.oak/221664	-
dc.description.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.	*
dc.language	English	*
dc.title	Unified predictor hypothesis tests in sufficient dimension reduction: A bootstrap approach	*
dc.type	Article	*
dc.relation.issue	2	*
dc.relation.volume	40	*
dc.relation.index	SCIE	*
dc.relation.index	SCOPUS	*
dc.relation.index	KCI	*
dc.relation.startpage	217	*
dc.relation.lastpage	225	*
dc.relation.journaltitle	Journal of the Korean Statistical Society	*
dc.identifier.doi	10.1016/j.jkss.2010.09.006	*
dc.identifier.wosid	WOS:000290823000012	*
dc.identifier.scopusid	2-s2.0-79954624493	*
dc.author.google	Yoo J.K.	*
dc.contributor.scopusid	유재근(23032759600)	*
dc.date.modifydate	20240130113500	*