IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4612-2856-1_53.html
   My bibliography  Save this book chapter

Comparison of Empirical Bayes and Extended Set Compound Rules for Classification of a Sequence of Crop Types

In: Computing Science and Statistics

Author

Listed:
  • K. L. D. Gunawardena

    (University of Wisconsin Oshkosh, Department of Mathematics)

Abstract

Hill et al. (1984) consider the application of parametric empirical Bayes theory to the classification of a sequence of crop types θ= (θ 1, θ 2,….), where each θ i = 0 or 1. The measurement vector Xi. is assumed to have density fθi (.) where both f0 and f1 are known. For fixed θ, the Xi’s are assumed to be independent. We consider the same problem, and obtain extended set compound rules for classifying the sequence of crop types.

Suggested Citation

  • K. L. D. Gunawardena, 1992. "Comparison of Empirical Bayes and Extended Set Compound Rules for Classification of a Sequence of Crop Types," Springer Books, in: Connie Page & Raoul LePage (ed.), Computing Science and Statistics, pages 357-360, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-2856-1_53
    DOI: 10.1007/978-1-4612-2856-1_53
    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

    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:978-1-4612-2856-1_53. 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.