A dynamic Poisson model is used with a Bayesian approach to modeling to predict cancer mortality. The complexity of the posterior distribution prohibits direct evaluation of the posterior, and so parameters are estimated by using a Markov Chain Monte Carlo method. The model is applied to analyze lung and stomach cancer data which have been collected in Japan.
Midorikawa, Shuichi; Miyaoka, Etsuo; and Smith, Bruce
"Application of Dynamic Poisson Models to Japanese Cancer Mortality Data,"
Journal of Modern Applied Statistical Methods:
2, Article 22.
Available at: http://digitalcommons.wayne.edu/jmasm/vol7/iss2/22