On the extension of sliced average variance estimation to multivariate regression

Jae Keun Yoo, Keunbaik Lee, Seongho Wu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Many sufficient dimension reduction methods for univariate regression have been extended to multivariate regression. Sliced average variance estimation (SAVE) has the potential to recover more reductive information and recent development enables us to test the dimension and predictor effects with distributions commonly used in the literature. In this paper, we aim to extend the functionality of the SAVE to multivariate regression. Toward the goal, we propose three new methods. Numerical studies and real data analysis demonstrate that the proposed methods perform well.

Original languageEnglish
Pages (from-to)529-540
Number of pages12
JournalStatistical Methods and Applications
Volume19
Issue number4
DOIs
StatePublished - 2010

Keywords

  • Double slicing
  • K-means clustering
  • Multivariatere gression
  • Pooled estimation
  • Sliced average variance estimation

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