IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4613-9464-8_46.html
   My bibliography  Save this book chapter

A kTH Nearest Neighbour Clustering Procedure

In: Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface

Author

Listed:
  • M. Anthony Wong

    (Massachusetts Institute of Technology)

  • Tom Lane

    (Massachusetts Institute of Technology)

Abstract

Due to the lack of development in the probabilistic and statistical aspects of clustering research. clustering procedures are often regarded as heuristics generating artificial clusters from a given set of sample data. In this paper, a clustering procedure that is useful for drawing statistical inference about the underlying population from a random sample is developed. It is based on the uniformly consistent kth nearest neighbour density estimate. and is applicable to both case-by-variable data matrices and case-by-case dissimilarity matrices. The proposed clustering procedure is shown to be asymptotically consistent for high-density clusters in several dimensions. and its small-sample behavior is illustrated by empirical examples.

Suggested Citation

  • M. Anthony Wong & Tom Lane, 1981. "A kTH Nearest Neighbour Clustering Procedure," Springer Books, in: William F. Eddy (ed.), Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface, pages 308-311, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4613-9464-8_46
    DOI: 10.1007/978-1-4613-9464-8_46
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:spr:sprchp:978-1-4613-9464-8_46. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.