Absolute moments in terms of characteristic functions

Gwo Dong Lin, Chin-Yuan Hu

Published 2018-09-20Version 1

The absolute moments of probability distributions are more complicated than conventional ones. By using a direct and simpler approach, we retreat P. L. Hsu's (1951, J. Chinese Math. Soc., Vol. 1, pp. 257-280) formulas in terms of the characteristic function and provide some new results as well. The case of nonnegative random variables is also investigated through both characteristic function and Laplace-Stieltjes transform. Besides, we prove that the distribution of a nonnegative random variable with a finite fractional moment can be completely determined by a proper subset of the translated fractional moments. This improves significantly Hall's (1983) result for distributions on the right-half line.