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Computational Statistics

, Volume 18, Issue 3, pp 565–583 | Cite as

BITE: A Bayesian Intensity Estimator

  • Tommi Härkänen
Article

Summary

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.

Key words

Data augmentation Event history data analysis Interval censoring Multistate model Software package Survival analysis 

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Copyright information

© Physica-Verlag 2003

Authors and Affiliations

  • Tommi Härkänen
    • 1
  1. 1.Rolf Nevanlinna InstituteUniversity of HelsinkiFinland

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