Calendar and Notes

 

 WEEK   DATES    TOPIC  NOTES 
 WEEK 1 04/01 -- 04/05   Introduction. Description of the syllabus. Background material slides1.pdf
      slides2.pdf
 WEEK 2 04/08 -- 04/12   Large sample inference 
  Chp. 4, Chp. 10, 13.3		 slides3.pdf
      The multinomial and the multivariate normal models. 
  3.5,3.6		 slides4.pdf
 WEEK 3 04/15 -- 04/19   Hierarchical models and meta-analysis. 
  5.1-5.6

slides5.pdf
slides6.pdf
      Model Checking. 
  6.1-6.5 

slides7.pdf 
 WEEK 4 04/22 -- 04/26   Model comparison. 
  7.1-7.4 
  Test 1 (30%, 04/24)

slides8.pdf 
slides9.pdf 
      Accounting for data collection schemes. 
  8.1-8.5		  
 WEEK 5 04/29 -- 05/03   Observational studies. Censoring and truncation. 
  8.6-8.8		  
      Auxiliary variables for Monte Carlo methods. 
  12.1		  
 WEEK 6 05/06 -- 05/10   Regression models. 
  14.1-14.8		 slides10.pdf 
      Regression models. 
  14.1-14.8 		 slides11.pdf
 WEEK 7 05/13 -- 05/17

  Test 2 (30%, 05/15)

  
      G-priors. Regularization. Robust Inference. 
  17.1-17.5

slides12.pdf
R code
 WEEK 8 05/20 -- 05/24   Mixture models. 
  22.1-22.5		  
      Mixture models. 
  22.1-22.5		  
 WEEK 9 05/29 -- 05/31   Posterior Modes. EM algorithm. 
  13.1-13.4  		 slides13.pdf 
  Memorial Day   Efficient Gibbs and Metropolis samplers. 
  12.1-12.3		 slides14.pdf 
 WEEK 10 06/03 - 06/07

  Approximations
  13.7
  Test 3 (30%, 06/07)

  
   

  Gaussian process models 
  21.1-21.5