Bayesian Smoothing of Lung Cancer Data in Tirol, Salzburg and Vorarlberg

Rose-Gerd Koboltschnig
2016 Austrian Journal of Statistics  
Due to the high variability ofML-estimates of relative risk in low population areas incidence ratios have to be smoothed before mapping. We fit a Bayesian hierarchical model where the posterior distribution of relative risks is simulated via a Markov Chain Monte Carlo technique.
doi:10.17713/ajs.v28i1.507 fatcat:qfvnrlai45etlfm7n6rmg2rc74