MAT 4381 Bayesian Inference
3 units
Mathematics
Faculty of Science
An introduction to the theory and practice of modern Bayesian inference. Choice of prior distributions and calculation of the posterior distribution for single and multi-parameter models. Computational approaches to Bayesian inference such as Markov Chain Monte Carlo and Gibbs sampling. Hierarchical and regression modelling in a Bayesian framework. Use of statistical software.
Components:
Lecture
Previously Offered Terms:
Winter
French Equivalent: