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Markov Beta and Gamma Processes for Modelling Hazard Rates
Luis E. Nieto-Barajas and Stephen G. Walker
Scandinavian Journal of Statistics
Vol. 29, No. 3 (Sep., 2002), pp. 413-424
Published by: Wiley on behalf of Board of the Foundation of the Scandinavian Journal of Statistics
Stable URL: http://www.jstor.org/stable/4616724
Page Count: 12
You can always find the topics here!Topics: Markov processes, Markov models, Bayesian analysis, Bayes estimators, Statistical estimation, Burn in, Statistical models, Survival analysis, Censorship, Inference
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This paper generalizes the discrete time independent increment beta process of Hjort (1990), for modelling discrete failure times, and also generalizes the independnet gamma process for modelling piecewise constant hazard rates (Walker and Mallick, 1997). The generalizations are from independent increment to Markov increment prior processes allowing the modelling of smoothness. We derive posterior distributions and undertake a full Bayesian analysis.
Scandinavian Journal of Statistics © 2002 Board of the Foundation of the Scandinavian Journal of Statistics