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http://dx.doi.org/10.29220/CSAM.2021.28.5.553

More on directional regression  

Kim, Kyongwon (Department of Statistics, Ewha Womans University)
Yoo, Jae Keun (Department of Statistics, Ewha Womans University)
Publication Information
Communications for Statistical Applications and Methods / v.28, no.5, 2021 , pp. 553-562 More about this Journal
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
central subspace; fused sliced inverse regression; multivariate regression; pooled approach; sufficient dimension reduction;
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