More on directional regression

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)553-562
Number of pages10
JournalCommunications for Statistical Applications and Methods
Volume28
Issue number5
DOIs
StatePublished - 2021

Bibliographical note

Funding Information:
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). 1Co-Corresponding Author: Department of Statistics, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea. E-mail: kimk@ewha.ac.kr 2Co-Corresponding Author: Department of Statistics, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea. E-mail: peter.yoo@ewha.ac.kr

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

Keywords

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

Fingerprint

Dive into the research topics of 'More on directional regression'. Together they form a unique fingerprint.

Cite this