We develop a maximum relative entropy formalism to generate optimal approximations to probability distributions. The central results consist of (a) justifying the use of relative entropy as the uniquely natural criterion to select a preferred approximation from within a family of trial...

For good reasons, it is standard practice to remove trends before linearizing a growth model. This paper explores an alternative strategy that consists in computing local approximations around successive points in the state space. Obviously this is terribly inefficiant it trend removal is...