More on directional regression

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Directional regression (DR; Li and Wang, 2007) is well-known as an exhaustive sufficient dimension reduction method, and performs well in complex regression models to have linear and nonlinear trends. However, the extension of DR is not well-done upto date, so we will extend DR to accommodate multivariate regression and large p-small n regression. We propose three versions of DR for multivariate regression and discuss how DR is applicable for the latter regression case. Numerical studies confirm that DR is robust to the number of clusters and the choice of hierarchical-clustering or pooled DR.

Original languageEnglish
Pages (from-to)553-562
Number of pages10
JournalCommunications for Statistical Applications and Methods
Issue number5
StatePublished - 2021

Bibliographical note

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© 2021. The Korean Statistical Society, and Korean International Statistical Society. All rights reserved.


  • central subspace
  • fused sliced inverse regression
  • multivariate regression
  • pooled approach
  • sufficient dimension reduction


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