Bayesian spatial statistics and modeling represent a robust inferential framework where uncertainty in spatial processes is explicitly quantified through probability distributions. This approach ...

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 51, No. 3 (2002), pp. 257-280 (24 pages) We model daily catches of fishing boats in the Grand Bank fishing grounds. We use ...

Occupational and Environmental Medicine, Vol. 66, No. 8 (August 2009), pp. 502-508 (7 pages) Objectives: Residual confounding can be present in epidemiological studies because information on ...

Here’s our estimate of public support for vouchers, broken down by religion/ethnicity, income, and state: (Click on image to see larger version.) We’re mapping estimates from a hierarchical Bayes ...

Bayesian networks are powerful tools in probabilistic reasoning, allowing us to model complex systems where uncertainty and causal relationships intertwine. At their core, Bayesian Networks are ...