Bayesian Analysis

Graduate course, Rutgers University (16:960:568), semester(s) offered: 2021s, 2022s, 2023s

Overview

An introduction to Bayesian statistical modeling, inference, and computation. Single- and multi-parameter models, hierarchical models, model checking, evaluation, selection, sensitivity analysis and prediction. Bayesian decision analysis. Monte Carlo and Markov chain Monte Carlo (Metropolis-Hastings, Gibbs). Select topics in advanced Bayesian computation, e.g. Hamiltonian Monte Carlo and approximate Bayesian computation.

Textbook

  • Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian data analysis. CRC press.