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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2017.9
- 수록면
- 1,167 - 1,177 (11page)
이용수
초록· 키워드
오류제보하기
The censored regression using the pseudo-response variable proposed by Buckley and James has been one of the most well-known models. Recently, the varying coefficient regression model has received a great deal of attention as an important tool for modeling. In this paper we propose a censored varying coefficient regression model using Buckley-James method to consider situations where the regression coefficients of the model are not constant but change as the smoothing variables change. By using the formulation of least squares support vector machine (LS-SVM), the coefficient estimators of the proposed model can be easily obtained from simple linear equations. Furthermore, a generalized cross validation function can be easily derived. In this paper, we evaluated the proposed method and demonstrated the adequacy through simulate data sets and real data sets.
목차
Abstract
1. Introduction
2. Censored regression
3. Varying coefficient regression model with censored data using LS-SVM
4. Numerical studies
5. Conclusions
References
참고문헌 (18)
참고문헌 신청
Buckley, J. and James, I. (1979). Linear regression with censored data. Biometrika, 66, 429-436.
Craven, P. andWahba, G. (1979). Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation. Numerical Mathematics, 31, 377-403.
Fan, J. and Zhang, W. (2008). Statistical methods with varying coefficient models. Statistics and Its Interface, 1, 179-195.
Hastie, T. and Tibshirani, R. (1993). Varying-coecient models. Journal of the Royal Statistical Society: Series B, 55, 757-796.
Hoover, D. R., Rice, J. A., Wu, C. O. and Yang, L. P. (1998). Nonparametric smoothing estimates of time-varying coefficient models with longitudinal data. Biometrika, 85, 809-822.
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UCI(KEPA) : I410-ECN-0101-2018-041-001796463