IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2009i5p1818-1828.html
   My bibliography  Save this article

Estimation of graphical models whose conditional independence graphs are interval graphs and its application to modelling linkage disequilibrium

Author

Listed:
  • Thomas, Alun

Abstract

Estimation of graphical models whose conditional independence graph comes from the general class of decomposable graphs is compared with estimation under the more restrictive assumption that the graphs are interval graphs. This restriction is shown to improve the mixing of the Markov chain Monte Carlo search to find an optimal model with little effect on the haplotype frequencies implied by the estimates. A further restriction requiring intervals to cover specified points is also considered and shown to be appropriate for modelling associations between alleles at genetic loci. As well as usefully describing the patterns of associations, these estimates can also be used to model population haplotype frequencies in statistical gene mapping methods such as linkage analysis and association studies.

Suggested Citation

  • Thomas, Alun, 2009. "Estimation of graphical models whose conditional independence graphs are interval graphs and its application to modelling linkage disequilibrium," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1818-1828, March.
  • Handle: RePEc:eee:csdana:v:53:y:2009:i:5:p:1818-1828
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00054-6
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hojsgaard, Soren & Thiesson, Bo, 1995. "BIFROST -- Block recursive models induced from relevant knowledge, observations, and statistical techniques," Computational Statistics & Data Analysis, Elsevier, vol. 19(2), pages 155-175, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Adele Marshall & Barry Shaw, 2014. "Computational learning of the conditional phase-type (C-Ph) distribution," Computational Management Science, Springer, vol. 11(1), pages 139-155, January.
    2. Højsgaard, Søren, 1996. "Learning structures from data and experts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 42(2), pages 143-152.
    3. Hojsgaard, Soren, 2003. "Split models for contingency tables," Computational Statistics & Data Analysis, Elsevier, vol. 42(4), pages 621-645, April.
    4. Thomas, Alun & Green, Peter J., 2009. "Enumerating the decomposable neighbors of a decomposable graph under a simple perturbation scheme," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1232-1238, February.

    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:eee:csdana:v:53:y:2009:i:5:p:1818-1828. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.