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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국통계학회 CSAM(Communications for Statistical Applications and Methods) CSAM(Communications for Statistical Applications and Methods) 제28권 제5호
- 발행연도
- 2021.9
- 수록면
- 553 - 562 (10page)
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초록· 키워드
오류제보하기
Directional regression (DR; Li and Wang, 2007) is well-known as an exhaustive sucient 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.
목차
Abstract
1. Introduction
2. Directional regression
3. Directional regression on multivariate regression
4. Direction regression in large p–small n data
5. Numerical studies and data analysis
6. Discussion
References
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