Laplace’s rule of succesion is often used by forecasters to set base rates. What does he think of that? Is this a good rule of thumb?
Moreover, Laplace’s rule gives different results depending on how finely you subdivide time (eg saying that there has been one year of global pandemic in the last 20 years will give different results that if you say there has been 12 months of pandemic in the last 20*12 months). How should we account for that inconsistency when applying Laplace’s law?
Laplace’s rule of succesion is often used by forecasters to set base rates. What does he think of that? Is this a good rule of thumb?
Moreover, Laplace’s rule gives different results depending on how finely you subdivide time (eg saying that there has been one year of global pandemic in the last 20 years will give different results that if you say there has been 12 months of pandemic in the last 20*12 months). How should we account for that inconsistency when applying Laplace’s law?
How should one aggregate different forecasts? Is External Bayesianity a compelling criteria for an aggregation procedure? How about marginalization?