IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-7908-1709-6_24.html
   My bibliography  Save this book chapter

Identifying excessively rounded or truncated data

In: Compstat 2006 - Proceedings in Computational Statistics

Author

Listed:
  • Kevin H. Knuth

    (University at Albany, Department of Physics)

  • J. Patrick Castle

    (NASA Ames Research Center, Intelligent Systems Division)

  • Kevin R. Wheeler

    (Monterey Bay Aquarium Research Institute)

Abstract

All data are digitized, and hence are essentially integers rather than true real numbers. Ordinarily this causes no difficulties since the truncation or rounding usually occurs below the noise level. However, in some instances, when the instruments or data delivery and storage systems are designed with less than optimal regard for the data or the subsequent data analysis, the effects of digitization may be comparable to important features contained within the data. In these cases, information has been irrevocably lost in the truncation process. While there exist techniques for dealing with truncated data, we propose a straightforward method that will allow us to detect this problem before the data analysis stage. It is based on an optimal histogram binning algorithm that can identify when the statistical structure of the digitization is on the order of the statistical structure of the data set itself.

Suggested Citation

  • Kevin H. Knuth & J. Patrick Castle & Kevin R. Wheeler, 2006. "Identifying excessively rounded or truncated data," Springer Books, in: Alfredo Rizzi & Maurizio Vichi (ed.), Compstat 2006 - Proceedings in Computational Statistics, pages 313-323, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-1709-6_24
    DOI: 10.1007/978-3-7908-1709-6_24
    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:978-3-7908-1709-6_24. 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.