This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...

Bayesian inference has emerged as a powerful tool in the analysis of queueing systems, blending probability theory with statistical estimation to update beliefs about system parameters as new data ...

Current course names and descriptions are available below; please note they are subject to change. You can also search for current and past course offerings on UAB's Class Schedule Listing site.

We consider Bayesian inferences on a type of multivariate median and the multivariate quantile functionals of a joint distribution using a Dirichlet process prior. Unlike univariate quantiles, the ...

We estimate by Bayesian inference the mixed conditional heteroskedasticity model of Haas et al. (2004a Journal of Financial Econometrics 2, 211–50). We construct a Gibbs sampler algorithm to compute ...