Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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More on directional regression

  • Kim, Kyongwon (Department of Statistics, Ewha Womans University) ;
  • Yoo, Jae Keun (Department of Statistics, Ewha Womans University)
  • Received : 2021.05.05
  • Accepted : 2021.05.24
  • Published : 2021.09.30
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Abstract

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.

Keywords

Acknowledgement

For Kyongwon Kim, this work was supported by the Ewha Womans University Research Grant of 2021 and the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No.2021R1F1A1046976) For Jae Keun Yoo, this work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Korean Ministry of Education (NRF-2021R1F1A1059844).

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