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A fast compact algorithm for cubic spline smoothing

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  • Weinert, Howard L.

Abstract

An efficient algorithm is presented for computing discrete or continuous cubic smoothing splines with uniformly spaced and uniformly weighted measurements. The algorithm computes both the spline values and the generalized cross-validation score. Execution time and memory use are reduced by carefully exploiting the problem's rich structure. The frequency domain properties of the steady-state cubic spline smoother are also examined.

Suggested Citation

  • Weinert, Howard L., 2009. "A fast compact algorithm for cubic spline smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 932-940, February.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:4:p:932-940
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    References listed on IDEAS

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    1. Weinert, Howard L., 2007. "Efficient computation for Whittaker-Henderson smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 959-974, October.
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    1. Bertolazzi, Enrico & Frego, Marco & Biral, Francesco, 2020. "Point data reconstruction and smoothing using cubic splines and clusterization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 176(C), pages 36-56.

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