In this post I’ll demonstrate one way to use Bayesian methods to build a ‘dynamic’ or ‘learning’ regression model. When I say ‘learning,’ I mean that it can elegantly adapt to new observations without requiring a refit.
Today we lay our scene in London between the years 1760-1850. The good people of London have bread and they have wheat, which is, of course, what bread is made from. One would expect that the price of bread and the price of wheat are closely correlated and generally they are, though in periods of turmoil things can come unstuck. And Europe, between 1760-1850, was a very eventful place.