IDEAS home Printed from
   My bibliography  Save this article

Automatic bandwidth selection for circular density estimation


  • Taylor, Charles C.


Given angular data [theta]1,...,[theta]n[set membership, variant][0,2[pi]) a common objective is to estimate the density. In case that a kernel estimator is used, bandwidth selection is crucial to the performance. A "plug-in rule" for the bandwidth, which is based on the concentration of a reference density, namely, the von Mises distribution is obtained. It is seen that this is equivalent to the usual Euclidean plug-in rule in the case where the concentration becomes large. In case that the concentration parameter is unknown, alternative methods are explored which are intended to be robust to departures from the reference density. Simulations indicate that "wrapped estimators" can perform well in this context. The methods are applied to a real bivariate dataset concerning protein structure.

Suggested Citation

  • Taylor, Charles C., 2008. "Automatic bandwidth selection for circular density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3493-3500, March.
  • Handle: RePEc:eee:csdana:v:52:y:2008:i:7:p:3493-3500

    Download full text from publisher

    File URL:
    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

    1. K. V. Mardia, 1999. "Directional statistics and shape analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 949-957.
    2. Agostinelli, Claudio, 2007. "Robust estimation for circular data," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5867-5875, August.
    3. Klemelä, Jussi, 2000. "Estimation of Densities and Derivatives of Densities with Directional Data," Journal of Multivariate Analysis, Elsevier, vol. 73(1), pages 18-40, April.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Oliveira, María & Crujeiras, Rosa M. & Rodríguez-Casal, Alberto, 2014. "NPCirc: An R Package for Nonparametric Circular Methods," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i09).
    2. García-Portugués, Eduardo & Crujeiras, Rosa M. & González-Manteiga, Wenceslao, 2013. "Kernel density estimation for directional–linear data," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 152-175.
    3. Lombard, F. & Hawkins, Douglas M. & Potgieter, Cornelis J., 2017. "Sequential rank CUSUM charts for angular data," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 268-279.
    4. repec:eee:csdana:v:56:y:2012:i:12:p:3898-3908 is not listed on IDEAS
    5. Giwhyun Lee & Yu Ding & Marc G. Genton & Le Xie, 2015. "Power Curve Estimation With Multivariate Environmental Factors for Inland and Offshore Wind Farms," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 56-67, March.
    6. repec:bla:scjsta:v:44:y:2017:i:1:p:249-267 is not listed on IDEAS
    7. Schoch, Tobias & Staub, Kaspar & Pfister, Christian, 2012. "Social inequality and the biological standard of living: An anthropometric analysis of Swiss conscription data, 1875–1950," Economics & Human Biology, Elsevier, vol. 10(2), pages 154-173.

    More about this item


    Access and download statistics


    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:52:y:2008:i:7:p:3493-3500. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.