Fitting continuous probability density functions over [0,infty) using information theory ideas (Corresp.)

The problem of estimating a probability density functionp(x)over[0, ∞)when several low-order moments are known is considered. A computational procedure, based on information theory, is used to obtain the maximum entropy estimates ofp(x)in a number of cases. The situation when the first two moments only are known is considered in some detail. A table is included for estimatingp(x)when givenμ_1 ^{} , μ_2 ^{}withμ_2 ^{} ≤ 2(μ_1 ^{}) ^ 2.