IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-7908-2656-2_39.html
   My bibliography  Save this book chapter

Exploratory Visual Analysis of Graphs in GGOBI

In: COMPSTAT 2004 — Proceedings in Computational Statistics

Author

Listed:
  • Deborah F. Swayne

    (AT&T Labs — Research)

  • Andreas Buja

    (University of California, The Wharton School University of Pennsylvania Duncan Temple Lang)

Abstract

Graphs have long been of interest in telecommunications and social network analysis, and they are now receiving increasing attention from statisticians working in other areas, particularly in biostatistics. Most of the visualization software available for working with graphs has come from outside statistics and has not included the kind of interaction that statisticians have come to expect. At the same time, most of the exploratory visualization software available to statisticians has made no provision for the special structure of graphs. Graphics software for the exploratory visual analysis of graph data should include the following: graph layout methods; a variety of displays and methods for exploring variables on both nodes and edges, including methods that allow these covariate displays to be linked to the network view; methods for thinning or otherwise trimming a large graph. In addition, the power of the visualization software is greater if it can be smoothly linked to an extensible and interactive statistics environment. In this paper, we will describe how these goals have been addressed in GGobi through its data format, architecture, graphical user interface design, and its relationship to the R software [7].

Suggested Citation

  • Deborah F. Swayne & Andreas Buja, 2004. "Exploratory Visual Analysis of Graphs in GGOBI," Springer Books, in: Jaromir Antoch (ed.), COMPSTAT 2004 — Proceedings in Computational Statistics, pages 477-488, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2656-2_39
    DOI: 10.1007/978-3-7908-2656-2_39
    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:978-3-7908-2656-2_39. 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.