MEES612

This seminar will explore the advanced practices of Bayesian network, and graphical model to high dimensional inter-disciplinary, environmental data. Through hands-on experience and real studies, from Bayesian perspectives, students will learn the basics of evaluating, Bayesian network and graphical analyses, and interpreting and, communicating the results. Case studies involving ecological and, environmental science will be used to illustrate Bayesian analyses. The, statistical programming language R and software packages such as, OpenBUGS, JAGS, and STAN will be used in illustrating Bayesian, models.