IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v18y2003i3p565-583.html
   My bibliography  Save this article

BITE: A Bayesian Intensity Estimator

Author

Listed:
  • Tommi Härkänen

Abstract

BITE is a software package designed for the analysis of event history data using flexible hierarchical models and Bayesian inference, with a particular emphasis on the application of flexible intensities as a description of the distribution of lifetimes. BITE provides a framework for combining flexible baseline hazard rates and observed data into intensity processes. Inclusion of covariate information is possible, and data can be non-informatively and independently filtered, or censored. The model and the data are described by a command language and data are stored into text files. Markov chain Monte Carlo methods are used for numerical approximation of expectations with respect to the posterior. Output consists of (i) parameter values stored during simulations, (ii) estimated expectations of functionals of parameters, or (iii) graphs (created with Splus or R software packages) presenting point-wise expectations (and credibility intervals) of the baseline hazard rates. Copyright Physica-Verlag 2003

Suggested Citation

  • Tommi Härkänen, 2003. "BITE: A Bayesian Intensity Estimator," Computational Statistics, Springer, vol. 18(3), pages 565-583, September.
    • Handle: RePEc:spr:compst:v:18:y:2003:i:3:p:565-583
    DOI: 10.1007/BF03354617
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF03354617
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF03354617?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    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:compst:v:18:y:2003:i:3:p:565-583. 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.