Bayesian analysis offers a robust framework for deciphering the intricate dynamics of time series data. By treating unknown parameters as random variables, this approach incorporates prior information ...

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 ...

Decision trees, influence diagrams, the value of information; Bayesian approaches, including conjugate and predictive distributions; utility theory foundations, risk preference, multiattribute utility ...

The project addresses the challenge that groundwater remediation strategies often fail because they ignore model uncertainty. The proposed research uses a multi-model data-worth analysis to improve ...