Fused sliced average variance estimation

Hyoin An, Sungmin Won, Jae Keun Yoo

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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
Issue number4
StatePublished - Dec 2017

Bibliographical note

Publisher Copyright:
© 2017 The Korean Statistical Society


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


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