BITE: A Bayesian Intensity Estimator. 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.
Keywords for this software
References in zbMATH (referenced in 6 articles , 1 standard article )
Showing results 1 to 6 of 6.
- Cai, Bo; Lin, Xiaoyan; Wang, Lianming: Bayesian proportional hazards model for current status data with monotone splines (2011)
- Mongoué-Tchokoté, Solange; Kim, Jong-Sung: New statistical software for the proportional hazards model with current status data (2008)
- Dreassi, Emanuela; Gottard, Anna: A Bayesian approach to model interdependent event histories by graphical models (2007)
- Komárek, Arnošt; Lesaffre, Emmanuel; Härkänen, Tommi; Declerck, Dominique; Virtanen, Jorma I.: A Bayesian analysis of multivariate doubly-interval-censored dental data (2005)
- Härkänen, T.; Arjas, E.: Tumour incidence, prevalence and lethality estimation in the absence of cause-of-death information (2004)
- Härkänen, Tommi: BITE: a Bayesian intensity estimator (2003)
Further publications can be found at: http://www.rni.helsinki.fi/~tth/biteref.html