STAT4010 Bayesian Learning (2023 Spring)

Tutorial Information

Time: Every Thursday 16:30-17:15
Venue: LSB LT2

  Tutorial Topics Notes Codes Remark
2-Feb-2023 01 Bayesian Philosophy, Posterior Calculation, R Review Note 01 tut1.R  
9-Feb-2023 02 Representation, Invariant Priors Note 02 tut2.R  
16-Feb-2023 03 Prior Design Note 03 tut3.R  
23-Feb-2023 04 Loss, Risk, and Bayes Estimator Note 04 tut4.R  
2-Mar-2023     \ \ Consultation Session
9-Mar-2023     \ \ Consultation Session
16-Mar-2023 05 Adimissibility, Minimax Estimator Note 05 tut5.R  
23-Mar-2023 06 Bayesian Test, Bayes Factor Note 06 tut6.R  
30-Mar-2023 07 Region Estimation, Coding Problems, Theoretical Justification Note 07 tut7.R  
6-Apr-2023 08 Trapezoidal Rule, Inverse Transform Sampling, Importance Sampling Note 08 tut8.R  
13-Apr-2023 09 Reweighting Importance Sampling, MH algorithm Note 09 tut9.R  
20-Apr-2023 10 Gibbs Sampler, MH within Gibbs Note 10 tut10.R  


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