Fused sliced average variance estimation
- 주제(키워드) Fusing , Inverse regression , Sliced average variance estimation , Sufficient dimension reduction
- 등재 SCIE, SCOPUS, KCI등재
- 발행기관 Korean Statistical Society
- 발행년도 2017
- URI http://www.dcollection.net/handler/ewha/000000149767
- 본문언어 영어
- Published As http://dx.doi.org/10.1016/j.jkss.2017.06.003
- 저작권 이화여자대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
In this paper, we propose an approach to combine the kernel matrices constructed by sliced average variance estimation (SAVE) with various numbers of slices. The proposed approach is called fused sliced average variance estimation (FSAVE). By fusing the information by usual SAVE applications with different slice numbers, the sensitivity to slices can be reduced, so the structural dimension estimation can be improved. Numerical studies confirm this, and a real data analysis is presented. © 2017 The Korean Statistical Society
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