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Improved smoothing spline regression by combining estimates of different smoothness

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  • Lee, Thomas C. M.

Abstract

This paper studies nonparametric regression using smoothing splines. It proposes a method that combines smoothing spline estimates of different smoothness to form a final improved estimate. This new method is straightforward to implement, computationally inexpensive, and gives reliable performances in simulations.

Suggested Citation

  • Lee, Thomas C. M., 2004. "Improved smoothing spline regression by combining estimates of different smoothness," Statistics & Probability Letters, Elsevier, vol. 67(2), pages 133-140, April.
    • Handle: RePEc:eee:stapro:v:67:y:2004:i:2:p:133-140
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    References listed on IDEAS

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    1. Lee, Thomas C. M., 2003. "Smoothing parameter selection for smoothing splines: a simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 139-148, February.
    2. Clifford M. Hurvich & Jeffrey S. Simonoff & Chih‐Ling Tsai, 1998. "Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 271-293.
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    Cited by:

    1. Yaeji Lim & Hee-Seok Oh & Ying Kuen Cheung, 2019. "Multiscale Clustering for Functional Data," Journal of Classification, Springer;The Classification Society, vol. 36(2), pages 368-391, July.
    2. Dongik Jang & Hee-Seok Oh & Philippe Naveau, 2017. "Identifying local smoothness for spatially inhomogeneous functions," Computational Statistics, Springer, vol. 32(3), pages 1115-1138, September.
    3. Dursun AYDIN & Ersin YILMAZ, 2017. "Bandwidth Selection Problem for Nonparametric Regression Model with Right-Censored Data," Romanian Statistical Review, Romanian Statistical Review, vol. 65(2), pages 81-104, June.
    4. Jang, Dongik & Oh, Hee-Seok, 2011. "Enhancement of spatially adaptive smoothing splines via parameterization of smoothing parameters," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1029-1040, February.

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