Bayesian classification and regression trees for predicting incidence of cryptosporidiosis: changes (%) in relative risks with 95% credible intervals from Bayesian spatiotemporal CAR models of cryptosporidiosis in Queensland, Australia
This dataset was gathered to predict the spatial distribution of the cryptosporidiosis infection using selected social-ecological factors and climate variables. Predictions were completed using a Bayesian CART (Classification and Regression Tree) model.
The dataset presents the changes (%) in relative risks with 95% credible intervals from Bayesian spatio-temporal CAR models of cryptosporidiosis in Queensland, Australia.
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