Absolute moments and Fourier-based probability metrics

We present a family of explicit formulae for evaluating absolute moments of probability measures on $\mathbb{R}^d$ in terms of Fourier transforms. As to the space of probability measures possessing finite absolute moments of an arbitrary order, we exploit our formulae to characterize its Fourier image and construct Fourier-based probability metrics which make the space complete. As applications, we compute absolute moments of those probability measures whose characteristic functions belong to the Scheonberg classes, estimate absolute moments of convolutions and investigate the asymptotic behavior of solutions to the heat-diffusion equations from a probability view-point.

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