References
- Breslow, N. (1974). Covariance analysis of censored survival data. Biometrics, 30, 89-99. https://doi.org/10.2307/2529620
- Cho, D. H., Shim, J. and Seok, K. H. (2010). Doubly penalized kernel method for heteroscedastic autore- gressive data. Journal of the Korean Data & Information Science Society, 21, 155-162.
- Cox, D. R. (1972). Regression models and life tables(with discussions). Journal of the Royal Statistical Society, B, 34, 187-220.
- Cox, D. R. (1975). Partial likelihood. Biometrika, 62, 269-276. https://doi.org/10.1093/biomet/62.2.269
- Craven, P. and Wahba, 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.
- Evers, L. and Messow, C. M. (2008). Sparse kernel methods for high-dimensional survival data. Bioinfor- matics, 24, 1632-1638. https://doi.org/10.1093/bioinformatics/btn253
- Fan, J. and Li, R. (2001). Variable selection via nonconcave penalized likelihood and its oracle properties. Journal of the American Statistical Association, 96, 348-1360.
- 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.
- Li, H. and Luan, Y. (2003). Kernel Cox regression models for linking gene expression profiles to censored survival data. Pacific Symposium on Biocomputing, 8, 865-876.
- 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.
- Sauerbrei, W. and Schumacher, M. (1992). A bootstrap resampling procedure for model building: Appli- cation to the Cox regression model. Statistical Medicine, 11, 2093-2099. https://doi.org/10.1002/sim.4780111607
- Saunders, C., Gammerman, A. and Vovk, V. (1998). Ridge regression learning algorithm in dual variables. Proceedings of the 15th International Conference on Machine Learning, 515-521.
- Schoelkopf, B., Burge, C. and Smola, A. (1998). Advances in kernel methods: Support vector learning, MIT Press, MA.
- Shim, J. (2005). Censored kernel ridge regression. Journal of the Korean Data & Information Science Society, 16, 1045-1052.
- Shim, J. and Lee, J. T. (2009). Kernel method for autoregressive data. Journal of the Korean Data & Information Science Society, 20, 467-472.
- Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society B, 58, 267-288.
- Tibshirani, R.(1997). The Lasso method for variable selection in the Cox model. Statistics in Medicine, 16, 385-395. https://doi.org/10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3
- Tsiatis, R. (1978). A heuristic estimate of the asymptotic variance of survival probability in Cox' regression model, Technical report of University of Wisconsin, number 524.
- Zhang, H. H. and Lu, W. (2007). Adaptive Lasso for Cox's proportional hazards model. Biometrika, 94, 691-703. https://doi.org/10.1093/biomet/asm037