convergence diagnostics

Pick anything below and it plays in the bar at the foot of the window — and keeps playing while you go on browsing the directory.

1. 1▶BDA course 2 extra: likelihood, normalization, density, model MBayesian Data AnalysisNotes
   +Watch later
2. 2▶BDA 2019 Lecture 7.2 exchangeabilityBayesian Data AnalysisNotes
   +Watch later
3. 3▶BDA 2019 Lecture 7.1 hierarchical modelsBayesian Data AnalysisNotes
   +Watch later
4. 4▶BDA 2019 Lecture 6.2 probabilistic programming and StanBayesian Data AnalysisNotes
   +Watch later
5. 5▶BDA 2019 Lecture 6.1 HMC, NUTS, dynamic HMC, and HMC specific convergence diagnosticsBayesian Data AnalysisNotes
   +Watch later
6. 6▶BDA 2019 Lecture 5.2 warm up, convergence diagnostics, R-hat, and effective sample sizeBayesian Data AnalysisNotes
   +Watch later
7. 7▶BDA 2019 Lecture 5.1 Markov chain Monte Carlo, Gibbs sampling, and Metropolis algorithmBayesian Data AnalysisNotes
   +Watch later
8. 8▶BDA 2019 Lecture 4.2 direct simulation, curse of dimensionality, rejection and importance samplingBayesian Data AnalysisNotes
   +Watch later
9. 9▶BDA 2019 Lecture 4.1 numerical issues, Monte Carlo, how many simulation draws are needed, ...Bayesian Data AnalysisNotes
   +Watch later
10. 10▶BDA 2019 Lecture 3 on multiparameter models. joint, marginal and conditional distribution, normalBayesian Data AnalysisNotes
    +Watch later