IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v39y1991i2p345-358.html
   My bibliography  Save this article

Density estimation for point processes

Author

Listed:
  • Ellis, Steven P.

Abstract

A general nonparametric density estimation problem is considered in which the data is generated by a spatial point process. Several practical problems are special cases of it, including those of estimating the common probability density of a sequence of random vectors and estimating the product density of a stationary multivariate point process. Kernel and k-nearest neighbor estimators are defined and in each case the joint asymptotic normality and consistency of the estimates of the density at a given finite number of points is derived.

Suggested Citation

  • Ellis, Steven P., 1991. "Density estimation for point processes," Stochastic Processes and their Applications, Elsevier, vol. 39(2), pages 345-358, December.
    • Handle: RePEc:eee:spapps:v:39:y:1991:i:2:p:345-358
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0304-4149(91)90087-S
    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.

    Citations

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


    Cited by:

    1. Pierre Jacob & Paulo Oliveira, 1999. "Histograms and Associated Point Processes," Statistical Inference for Stochastic Processes, Springer, vol. 2(3), pages 227-251, October.
    2. Dimitrios Tsitsis & George Karavasilis & Alexandros Rigas, 2012. "Measuring the association of stationary point processes using spectral analysis techniques," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(1), pages 23-47, March.
    3. Helmers, Roelof & Wayan Mangku, I. & Zitikis, Ricardas, 2003. "Consistent estimation of the intensity function of a cyclic Poisson process," Journal of Multivariate Analysis, Elsevier, vol. 84(1), pages 19-39, January.
    4. Florens, Danielle & Pham, Huyên, 1999. "Large deviation principle in nonparametric estimation of marked point processes," Statistics & Probability Letters, Elsevier, vol. 41(4), pages 383-388, February.

    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:spapps:v:39:y:1991:i:2:p:345-358. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/wps/find/journaldescription.cws_home/505572/description#description .

    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.