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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제21권 제3호
- 발행연도
- 2019.1
- 수록면
- 1,111 - 1,120 (10page)
이용수
초록· 키워드
오류제보하기
Variable selection is an important problem when the model includes many noisy variables. For years, the sparse penalized approaches have been proposed for the problem. Examples are the least absolute selection and shrinkage operator (LASSO) and smoothly clipped absolute deviation penalty. The sparse penalized approaches are known to have more stable sampling properties compared with the traditional best subset selection approaches, keeping higher computational efficiency. In this paper, we propose a new penalty, sparse net (SNET), that can be used for variable selection and parameter estimation in the linear regression model. The SNET consists of two penalties: the LASSO and the negative ridge. The SNET shares the same spirit with the elastic net but the ridge effect is negatively imposed on the regression coefficients to avoid unnecessary selection and biases. In general, the SNET penalized sum of squared residuals is non-convex, depending on the size of negative ridge effect, which requires non-convex optimization algorithm. For this issue, we introduce an efficient algorithm for implementing the SNET penalized estimator. Several numerical examples show that the SNET can be a nice competitor with existing penalties.
목차
등록된 정보가 없습니다.
참고문헌 (26)
참고문헌 신청
Breiman, L. / 1996 / Heuristics of instability and stabilization in model selection / The Annals of Statistics 24(6):2350~2383
Casella, G. / 1985 / An introduction to empirical Bayes data analysis / The American Statistician 39(2):83~87
전수영 / 2017 / 베이지안 부분집합 회귀를 이용한 고차원 분할표 분석 / Journal of The Korean Data Analysis Society 19(4):1841~1852
Efron, B. / 2004 / Least angle regression / The Annals of Statistics 32(2):407~499
Efron, B. / 1975 / Data analysis using Stein's estimator and its generalizations / Journal of the American Statistical Association 70(350):311~319
Casella, G. / 1985 / An introduction to empirical Bayes data analysis / The American Statistician 39(2):83~87
전수영 / 2017 / 베이지안 부분집합 회귀를 이용한 고차원 분할표 분석 / Journal of The Korean Data Analysis Society 19(4):1841~1852
Efron, B. / 2004 / Least angle regression / The Annals of Statistics 32(2):407~499
Efron, B. / 1975 / Data analysis using Stein's estimator and its generalizations / Journal of the American Statistical Association 70(350):311~319
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