We're soon rounding off!, having essentially been through all cofre material in the course, also having worked through a quite long list of exercises and stories. We meet a few more times, with themes asked for by you, the students -- we did minimaxity the other day, for instance.
For the coming few weeks: Find Olaf Bull's "Til de dristige", and reflect on its relevance for minimax strategies. Do exercises 7.6, the linex loss function, with concrete steps for the classic case of Y a \N(\theta, 1), and a \N(0,\sigma^2) prior for \theta. Then 7.7.?
We did Celine Cunen's Submarine (exam set 2018): show that the Bayes estimator there is the same as the sample mean of the two data points, and that it is unbiased. Which assumption, in the lemma which says that Bayes estimators are never unbiased, is not met??