I'm anderswo engagiert, on Tue Nov 5, but Gudmund Hermansen will teach, or perhaps rather give a mini-lecture, 9:15 to 11, with interruprtions and details, regarding a joint project of ours (which ought to be finished): Bayesian Nonparametrics for stationary Guassian time series. This is the thing: if y_1, y_2, ... are from such a time series, then there's a well-defined correlation function, which by the right theorem can be represented as
\corr(y_i, y_j) = 2 \int_0^\pi \cos( |j-i| \pi\omega)\,{{\rm d}}F(\omega,
for a suitable probability measure F on [0, \pi]. We may then put a Dirichlet process on this F, e.g. cented at the appropriate F_0 for an autoregressive process of some order, etc.
Thanks to Dennis Christensen for his 30-minute contribution last week; next week, Tue Nov 12, we're having
Maria Nareklishvili: Instrumental Variable Regression and its applications, Bayesian approach