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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.5
- 수록면
- 657 - 668 (12page)
- DOI
- 10.7465/jkdi.2021.32.3.657
이용수
초록· 키워드
오류제보하기
Robust estimation is widely used for analyzing statistical inference. We investigate penalized robust estimation via Welsch loss function with group Lasso method in high-dimensional linear regression models with group structure in this paper. This penalty identifies the significant groups of predictor variables. Robust estimation with group Lasso has crucial meaning in that it accompanies the large p (the number of predictors) small n (sample size) problems. We present the updating algorithms for this group Lasso problem. Compared with other penalty functions, we carried out simulation studies in order to assess the performance of the proposed method and the real dataset was demonstrated numerically for illustration purpose.
목차
Abstract
1. Introduction
2. Robust estimation
3. Penalized estimation with group Lasso
4. Numerical study
5. Concluding remarks
References
참고문헌 (32)
참고문헌 신청
Alon, U. / 1999 / Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays / PNAS 96:6745~6750
최경호 / 2019 / KOVO V-리그 경기력 요인의 상대적 중요도 탐색 / 한국데이터정보과학회지 30(4):771~778
Craven, P. / 1979 / Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation / Number. Math 31:337~403
Dennis Jr, JE. / 1978 / Techniques for nonlinear least squares and robust regression / Communications in Statistics-simulation and Computation 7:345~359
Donoho, D. L. / 1994 / Ideal spatial adaptation by wavelet shrinkage / Biometrika 81:425~455
최경호 / 2019 / KOVO V-리그 경기력 요인의 상대적 중요도 탐색 / 한국데이터정보과학회지 30(4):771~778
Craven, P. / 1979 / Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation / Number. Math 31:337~403
Dennis Jr, JE. / 1978 / Techniques for nonlinear least squares and robust regression / Communications in Statistics-simulation and Computation 7:345~359
Donoho, D. L. / 1994 / Ideal spatial adaptation by wavelet shrinkage / Biometrika 81:425~455
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UCI(KEPA) : I410-ECN-0101-2021-041-001749610