Intensive numerical studies of optimal sufficient dimension reduction with singularity
- 주제(키워드) Chi-square test , Optimality , Singularity , Sufficient dimension reduction
- 등재 SCOPUS, KCI등재
- 발행기관 Korean Statistical Society
- 발행년도 2017
- URI http://www.dcollection.net/handler/ewha/000000156430
- 본문언어 영어
- Published As http://dx.doi.org/10.5351/CSAM.2017.24.3.303
- 저작권 이화여자대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
Yoo (2015, Statistics and Probability Letters, 99, 109-113) derives theoretical results in an optimal sufficient dimension reduction with singular inner-product matrix. The results are promising, but Yoo (2015) only presents one simulation study. So, an evaluation of its practical usefulness is necessary based on numerical studies. This paper studies the asymptotic behaviors of Yoo (2015) through various simulation models and presents a real data example that focuses on ordinary least squares. Intensive numerical studies show that the X2 test by Yoo (2015) outperforms the existing optimal sufficient dimension reduction method. The basis estimation by the former can be theoretically sub-optimal; however, there are no notable differences from that by the latter. This investigation confirms the practical usefulness of Yoo (2015). © 2017 The Korean Statistical Society, and Korean International Statistical Society. All rights reserved.
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