Originally Posted by
Euler
Hi all, I'd like some suggestions about this. It seems to me that when you estimate the posterior probability, your priors are given equal weight (in the standard bayesian model), but in reality, priors ought to be given weights depending on how low ago they are, but how do account for this in your posterior estimates? Has anybody got any academic papers on the topic from either within sports gambling or outside sports gambling (social science surely has some answers, eg. more recent election polls are more important than less recent ones in predicting election outcomes anybody come across any papers?)