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5.10 文献笔记

原文	The Elements of Statistical Learning
翻译	szcf-weiya
发布	2017-06-09

样条和B样条在de Boor (1978)¹中有详细讨论．Green and Silverman (1994)²和Wahba (1990)给出了光滑样条以及thin-plate样条的；后者也产生核Hilbert空间．关于采用RKHS方法的非参回归技巧的联系可以参见Girosi et al. (1995)³ 和Evgeniou et al. (2000)⁴．如5.2.3节所示，对函数数据建模，在Ramsay and Silverman (1997)⁵中有详细介绍．

Daubechies (1992)⁶是一个经典的、小波的数学处理．其它有用的资源有Chui (1992)⁷和Wickerhauser (1994)⁸．Donoho and Johnstone (1994)⁹从统计估计的框架下发展了SURE收缩和选择的技巧；也可以参见Vidakovic (1999)¹⁰．Bruce and Gao (1996)¹¹是很有用的应用介绍，它也描述了S-PLUS中的小波软件．

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1. de Boor, C. (1978). A Practical Guide to Splines, Springer, New York. ↩

2. Green, P. and Silverman, B. (1994). Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach, Chapman and Hall, London. ↩

3. Girosi, F., Jones, M. and Poggio, T. (1995). Regularization theory and neural network architectures, Neural Computation 7: 219–269. ↩

4. Evgeniou, T., Pontil, M. and Poggio, T. (2000). Regularization networks and support vector machines, Advances in Computational Mathematics 13(1): 1–50. ↩

5. Ramsay, J. and Silverman, B. (1997). Functional Data Analysis, Springer, New York. ↩

6. Daubechies, I. (1992). Ten Lectures on Wavelets, Society for Industrial and Applied Mathematics, Philadelphia, PA. ↩

7. Chui, C. (1992). An Introduction to Wavelets, Academic Press, London. ↩

8. Wickerhauser, M. (1994). Adapted Wavelet Analysis from Theory to Software, A.K. Peters Ltd, Natick, MA. ↩

9. Donoho, D. and Johnstone, I. (1994). Ideal spatial adaptation by wavelet shrinkage, Biometrika 81: 425–455. ↩

10. Vidakovic, B. (1999). Statistical Modeling by Wavelets, Wiley, New York. ↩

11. Bruce, A. and Gao, H. (1996). Applied Wavelet Analysis with S-PLUS, Springer, New York. ↩

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