IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-4-431-65955-6_17.html
   My bibliography  Save this book chapter

Borrowing Strength from Images to Facilitate Exploratory Structural Analysis of Binary Variables

In: Measurement and Multivariate Analysis

Author

Listed:
  • Robert M. Pruzek

    (State University of New York at Albany)

Abstract

This paper concerns exploratory structural analysis of relations among binary variables. Some new methods are described and illustrated, methods that appear to hold promise for general improvements in binary structural analysis. Standard common factor theory and methods, including image analysis, are used in combination with methods for data smoothing, to construct an alternative data system at the outset of analysis. Most of the new algorithms are relatively fast, easy to explain and to program, and appear to work as intended, at least for initial applications with real and simulated data. Given various advances in statistical theory and methods for prediction, as well as increasingly powerful and convenient computing facilities, there are a number of ways to extend the methods discussed here beyond the current framework.

Suggested Citation

  • Robert M. Pruzek, 2002. "Borrowing Strength from Images to Facilitate Exploratory Structural Analysis of Binary Variables," Springer Books, in: Shizuhiko Nishisato & Yasumasa Baba & Hamparsum Bozdogan & Koji Kanefuji (ed.), Measurement and Multivariate Analysis, pages 163-174, Springer.
  • Handle: RePEc:spr:sprchp:978-4-431-65955-6_17
    DOI: 10.1007/978-4-431-65955-6_17
    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:978-4-431-65955-6_17. 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.