Ed Herbst

1. Introduction ·
2. A Crash Course in Bayesian Inference ·
3. Linear DSGE Models and the Kalman Filter ·
4. Monte Carlo Simulation ·
5. Metropolis Hastings ·
6. Sequential Monte Carlo ·
7. Estimating a Linear DSGE Model ·
8. Nonlinear DSGE Models and Particle Filters ·
9. PMCMC and SMC Squared ·
10. Hamiltonian Monte Carlo ·
11. Quasilinear Models

jupyter notebooks

1. Importance Sampling jupyter notebook
2. Metropolis-Hastings jupyter notebook
3. Particle Filtering jupyter notebook