지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국통계학회 CSAM(Communications for Statistical Applications and Methods) CSAM(Communications for Statistical Applications and Methods) 제28권 제2호
- 발행연도
- 2021.3
- 수록면
- 205 - 215 (11page)
이용수
초록· 키워드
오류제보하기
Sufficient dimension reduction is useful dimension reduction tool in regression, and sliced inverse regression (Li, 1991) is one of the most popular sufficient dimension reduction methodologies. In spite of its popularity, it is known to be sensitive to the number of slices. To overcome this shortcoming, the so-called fused sliced inverse regression is proposed by Cook and Zhang (2014). Unfortunately, the two existing methods do not have the direction application to large p-small n regression, in which the dimension reduction is desperately needed. In this paper, we newly propose seeded sliced inverse regression and seeded fused sliced inverse regression to overcome this deficit by adopting iterative projection approach (Cook et al., 2007). Numerical studies are presented to study their asymptotic estimation behaviors, and real data analysis confirms their practical usefulness in high-dimensional data analysis.
목차
Abstrac
1. Introduction
2. Sliced and fused sliced inverse regressions and nestness
3. Seeded sliced and seeded fused sliced inverse regressions
4. Numerical studies and data analysis
5. Discussion
References
참고문헌 (0)
참고문헌 신청함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Fused inverse regression with multi-dimensional responses
CSAM(Communications for Statistical Applications and Methods)
2021 .05
-
Fused sliced inverse regression in survival analysis
CSAM(Communications for Statistical Applications and Methods)
2017 .09
-
On robustness in dimension determination in fused sliced inverse regression
CSAM(Communications for Statistical Applications and Methods)
2018 .09
-
Tutorial: Methodologies for sufficient dimension reduction in regression
CSAM(Communications for Statistical Applications and Methods)
2016 .03
-
Model-based inverse regression for mixture data
CSAM(Communications for Statistical Applications and Methods)
2017 .01
-
Dimension reduction for right-censored survival regression: transformation approach
CSAM(Communications for Statistical Applications and Methods)
2016 .05
-
Fused sliced average variance estimation의 실증분석: 비스킷 반죽의 근적외분광분석법 분석 자료로의 적용
응용통계연구
2018 .12
-
More on directional regression
CSAM(Communications for Statistical Applications and Methods)
2021 .09
-
Intensive comparison of semi-parametric and nonparametric dimension reduction methods in forward regression
CSAM(Communications for Statistical Applications and Methods)
2022 .09
-
On the Lu Qi-Keng problem for slice monogenic functions
대한수학회보
2018 .01
-
Projections and slices of measures
대한수학회논문집
2021 .01
-
Tutorial: Dimension reduction in regression with a notion of sufficiency
CSAM(Communications for Statistical Applications and Methods)
2016 .03
-
On hierarchical clustering in sufficient dimension reduction
CSAM(Communications for Statistical Applications and Methods)
2020 .07
-
Riquier and Dirichlet boundary value problems for slice Dirac operators
대한수학회보
2018 .01
-
Intensive numerical studies of optimal sufficient dimension reduction with singularity
CSAM(Communications for Statistical Applications and Methods)
2017 .05
-
토양의 수분이동 특성 결정을 위한 inverse modeling
대한지질학회 학술대회
2019 .10
-
Note on response dimension reduction for multivariate regression
CSAM(Communications for Statistical Applications and Methods)
2019 .09
-
Note on the Generalized Invertibility of a-xy
Kyungpook Mathematical Journal
2015 .01
-
Weighted gDMP inverse of operators between Hilbert spaces
대한수학회보
2018 .01
-
A Note on Bootstrapping in Sufficient Dimension Reduction
CSAM(Communications for Statistical Applications and Methods)
2015 .05
이 논문의 저자 정보
최근 본 자료
댓글(0)
0
UCI(KEPA) : I410-ECN-0101-2023-310-001432410