TY - JOUR
T1 - Unified predictor hypothesis tests in sufficient dimension reduction
T2 - A bootstrap approach
AU - Yoo, Jae Keun
N1 - Funding Information:
For Jae Keun Yoo, this work was supported by a Basic Science Research Program through the National Research Foundation of Korea (KRF) funded by the Ministry of Education, Science and Technology ( 2010-0003189 ). The authors are also grateful to the referees for many helpful comments.
PY - 2011/6
Y1 - 2011/6
N2 - 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.
AB - 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.
KW - Bootstrapping
KW - Predictor hypothesis tests
KW - Sufficient dimension reduction
KW - Vector correlation coefficient
UR - http://www.scopus.com/inward/record.url?scp=79954624493&partnerID=8YFLogxK
U2 - 10.1016/j.jkss.2010.09.006
DO - 10.1016/j.jkss.2010.09.006
M3 - Article
AN - SCOPUS:79954624493
SN - 1226-3192
VL - 40
SP - 217
EP - 225
JO - Journal of the Korean Statistical Society
JF - Journal of the Korean Statistical Society
IS - 2
ER -