Advanced Bayesian Methods: Theory and Applications in R
Outline
Day 1
- Principles of Bayesian Inference
- Markov Chain Monte Carlo Simulations
- Monitoring Mixing and Convergence
- Posterior Summaries
- Penalized Spline Smoothing
- A Generic Basis Function Framework
Day 2
- Spatial Smoothing
- GAMLSS
- Model Checking
- Families
- Big Data and Variable Selection
- Machine Learning
Course Materials
Data and course materials are available at ABM.