1 |
Stute, W. (1993). Consistent estimation under random censorship when covariables are available. Journal of Multivariate Analysis, 45, 89=103.
DOI
ScienceOn
|
2 |
Suykens, J. A. K. and Vanderwalle, J. (1999). Least square support vector machine classifier. Neural Processing Letters, 9, 293-300.
DOI
|
3 |
Vapnik, V. N. (1998). Statistical learning theory, Wiley, New York.
|
4 |
Yang, S. (1999). Censored median regression using weighted empirical survival and hazard functions. Journal of the American Statistical Association, 94, 137-145.
DOI
ScienceOn
|
5 |
Ying, Z. L., Jung, S. H. and Wei, L. J. (1995). Survival analysis with median regression models, Journal of the American Statistical Association, 90, 178-184.
DOI
ScienceOn
|
6 |
Zhou, M. (1992). M-estimation in censored linear models. Biometrika, 79, 837-841.
DOI
|
7 |
Hwang, C. and Shim, J. (2010). Semiparametric support vector machine for accelerated failure time model. Journal of the Korean Data & Information Science Society, 21, 467-477.
|
8 |
Jin, Z., Lin, D. Y., Wei, L. J. and Ying, Z. L. (2003). Rank-based inference for the accelerated failure time model. Biometrika, 90, 341-353.
DOI
ScienceOn
|
9 |
Kaplan, E. L. and Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53, 457-481.
DOI
ScienceOn
|
10 |
Kimeldorf, G. and Wahba, G. (1981). Some results on Tchebychean spline functions. Journal of Mathematical Analysis and Applications, 33, 82-95.
|
11 |
Koul, H., Susarla, V. and Van Ryzin J. (1981). Regression analysis with randomly right censored data. The Annal of Statistics, 9, 1276-1288.
DOI
|
12 |
Mercer, J. (1909). Functions of positive and negative type and their connection with theory of integral equations. Philosophical Transactions of Royal Society A, 415-446.
|
13 |
Miller, R. G. (1976). Least squares regression with censored data. Biometrika, 63, 449-464.
DOI
ScienceOn
|
14 |
Shim, J., Kim, C. R. and Hwang, C. (2011). Semiparametric least squares support vector machine for accelerated failure time model. Journal of the Korean Statistical Society, 40, 75-83.
DOI
ScienceOn
|
15 |
Shim, J. (2005). Censored kernel ridge regression. Journal of the Korean Data & Information Science Society, 16, 1045-1052.
|
16 |
Shim, J. and Lee, J. T. (2009). Kernel method for autoregressive data. Journal of the Korean Data & Information Science Society, 20, 467-4720.
|
17 |
Heuchenne, C. and Van Keilegom, I. (2005). Nonlinear regression with censored data, Technometrics, 49, 34-44.
|
18 |
Smola, A. and Scholkopf, B. (1998). On a kernel-based method for pattern recognition, regression, approximation and operator inversion. Algorithmica, 22, 211-231.
DOI
|
19 |
Cho, D. H., Shim, J. and Seok, K. H. (2010). Doubly penalized kernel method for heteroscedastic autoregressive data. Journal of the Korean Data & Information Science Society, 21, 155-162.
|
20 |
Gunn, S. R. (1998). Support vector machines for classication and regression, Technical report, Department of Electronics and Computer Science, Southamption, England, United Kingdom.
|