References
- Aizerman, M. A., Braverman, E. M. and Rozonoer, L. I. (1964). Theoretical foundation of potential function method in pattern recognition learning. Automation and Remote Control, 25, 821-837.
- Anderson, T. G. and Lund, J. (1997). Estimating continuous-time stochastic volatility models of short-term interest rate. Journal of Econometrics, 77, 343-377. https://doi.org/10.1016/S0304-4076(96)01819-2
- Fan, J. Q. and Yao, Q. W. (1998). Efficient estimation of conditional variance functions in stochastic regression. Biometrika, 85, 645-660. https://doi.org/10.1093/biomet/85.3.645
- Golub, G. H., Heath, M. and Wahba, G. (1979). Generalized cross validation as a method for choosing a good ridge parameter. Technometrics, 21, 215-223. https://doi.org/10.2307/1268518
- Hwang, C. (2008). Mixed effects kernel binomial regression. Journal of Korean Data & Information Science Society, 19, 1327-1334.
- Juditsky, A, Hjalmarsson, H., Benveniste, A., Deylon, B., Ljung, L., Sj o. berg, J. and Zhang, Q. (1995). Nonlinear black-box modelling in system identification: Mathematical foundations. Automatica, 31, 1725-1750. https://doi.org/10.1016/0005-1098(95)00119-1
- Kimeldorf, G. S. and Wahba, G. (1971). Some results on Tchebycheffian spline functions. Journal of Mathematical Analysis and its Applications, 33, 82-95. https://doi.org/10.1016/0022-247X(71)90184-3
- Liu, A., Tong, T. and Wang, Y. (2007). Smoothing spline estimation of variance functions. Journal of Computational and Graphical Statistics, 16, 312-329. https://doi.org/10.1198/106186007X204528
- 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. https://doi.org/10.1098/rsta.1909.0016
- Ruppert, D., Wand, M. P., Holst, U. and Hossjer, O. (1997). Local polynomial variance-function estimation. Technometrics, 39, 262-73. https://doi.org/10.2307/1271131
- Shim, J. and Lee, J. T. (2009). Kernel method for autoregressive data. Journal of Korean Data and Information Science Society, 20, 949-954.
- Shim, J., Park, H. J. and Seok, K. H. (2008). Kernel Poisson regression for longitudinal data. Journal of Korean Data & Information Science Society, 19, 1353-1360.
- Shim, J., Park, H. J. and Seok, K. H. (2009). Variance function estimation with LS-SVM for replicated data. Journal of Korean Data and Information Science Society, 20, 925-931.
- Suykens, J. A. K. and Vanderwalle, J. (1999). Least square support vector machine classifier. Neural Processing Letters, 9, 293-300. https://doi.org/10.1023/A:1018628609742
- Xiang, D. and Wahba, G. (1996). A generalized approximate cross validation for smoothing splines with non-gaussian data. Statistian Sinica, 6, 675-692.
- Yuan, M. and Wahba, G. (2004). Doubly penalized likelihood estimator in heteroscedastic regression. Statistics & Probability Letters, 69, 11-20. https://doi.org/10.1016/j.spl.2004.03.009