IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2009i4p932-940.html
   My bibliography  Save this article

A fast compact algorithm for cubic spline smoothing

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00504-5
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Weinert, Howard L., 2007. "Efficient computation for Whittaker-Henderson smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 959-974, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ruixue Du & Hiroshi Yamada, 2020. "Principle of Duality in Cubic Smoothing Spline," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    2. Garcin, Matthieu, 2017. "Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 462-479.
    3. Garcia, Damien, 2010. "Robust smoothing of gridded data in one and higher dimensions with missing values," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1167-1178, April.
    4. Hiroshi Yamada & Ruoyi Bao, 2022. "$$\ell _{1}$$ ℓ 1 Common Trend Filtering," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1005-1025, March.
    5. Hiroshi Yamada, 2023. "Quantile regression version of Hodrick–Prescott filter," Empirical Economics, Springer, vol. 64(4), pages 1631-1645, April.
    6. Dermoune Azzouz & Djehiche Boualem & Rahmania Nadji, 2009. "Multivariate Extension of the Hodrick-Prescott Filter-Optimality and Characterization," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-35, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:53:y:2009:i:4:p:932-940. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.