exercises for Tue Oct 1

For Tue Oct 1, I will discuss the Dirichlet processes further, including their application to clustering processes, and then go on to Gamma-Poisson processes, see Lecture Notes Exercises 20, 21, 22, 23, 24.

For exercises: First, do the following. Generate  a dataset of size n = 50, from the unit exponential model. Consider the three parameters \xi = the mean, \sigma = the standard deviation, \gamma = the skewness (without "knowing" that the data are exponential). (a) Estimate the parameters. (b) Carry out Efron classical bootstrap, to assess their uncertainty. (c) Carry out Bayesian bootstrapping, to do the same. (d) Compare.

Then: do Nils Exercises 20, 21A, 21B, 22, 23.