STAT4010 Bayesian Learning (2023 Spring)

Tutorial Information

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

 TutorialTopicsNotesCodesRemark
2-Feb-202301Bayesian Philosophy, Posterior Calculation, R ReviewNote 01tut1.R 
9-Feb-202302Representation, Invariant PriorsNote 02tut2.R 
16-Feb-202303Prior DesignNote 03tut3.R 
23-Feb-202304Loss, Risk, and Bayes EstimatorNote 04tut4.R 
2-Mar-202305Adimissibility, Minimax EstimatorNote 05tut5.R 
9-Mar-2023  \\Consultation Session
16-Mar-2023  \\Consultation Session
23-Mar-202306Bayesian Test, Bayes FactorNote 06tut6.R 
30-Mar-202307Region Estimation, Coding Problems, Theoretical JustificationNote 07tut7.R 
6-Apr-202308Trapezoidal Rule, Inverse Transform Sampling, Importance SamplingNote 08tut8.R 
13-Apr-202309Reweighting Importance Sampling, MH algorithmNote 09tut9.R 
20-Apr-202310Gibbs Sampler, MH within GibbsNote 10tut10.R 

References

  1. Course Website (This is your major reference for revision.)
  2. E-learning Platform (You may want to check the platform before bringing questions to us.)