Fused sliced average variance estimation

Hyoin An, Sungmin Won, Jae Keun Yoo

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)623-628
Number of pages6
JournalJournal of the Korean Statistical Society
Volume46
Issue number4
DOIs
StatePublished - Dec 2017

Keywords

  • Fusing
  • Inverse regression
  • Sliced average variance estimation
  • Sufficient dimension reduction

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