Note that I have uploaded ¡­

Note that I have uploaded more R script files: com36c (exact vs. approximate posterior for Cauchy data), com40b (Poisson regression for airline accident data), com46a (Exam 2004, no. 4).

Exercises for Mon Nov 3:

Exam stk 4020 from 2004, no. 4: find ML estimates of (k, p0).

Use a modified version of com36c to assess exact and approximative posteriors for Cauchy data, with a couple of "strange" priors. How fast do data wash away the prior?

Finish 3.12, Poisson regression for airline data, with (a) normal prior-free approximation to posterior and (b) with the real prior that takes log(alpha) and beta to be independent normals N(log(20),sigma1^2) and N(0,sigma2^2), with values of sigma1 and sigma2 chosen by yourself.

Exam stk 4020 from 2004, no. 3.