IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2009i12p3916-3920.html
   My bibliography  Save this article

On hierarchical loglinear models in capture-recapture studies

Author

Listed:
  • You, Na
  • Mao, Chang Xuan

Abstract

Hierarchical loglinear models are widely used in capture-recapture studies. It is important to implement these models so that a full model selection procedure can be carried out. An algorithm used to count the number of monotone boolean functions is adopted to generate all the monotone boolean functions, which in turn is used to generate all coefficient matrices of hierarchical loglinear models. The proposed methods are implemented in an R package. Two real examples are analyzed for illustration.

Suggested Citation

  • You, Na & Mao, Chang Xuan, 2009. "On hierarchical loglinear models in capture-recapture studies," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 3916-3920, October.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:12:p:3916-3920
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(09)00165-0
    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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chang Xuan Mao & Ruochen Huang & Sijia Zhang, 2017. "Petersen estimator, Chapman adjustment, list effects, and heterogeneity," Biometrics, The International Biometric Society, vol. 73(1), pages 167-173, March.

    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:12:p:3916-3920. 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: 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.