Fourier-Legendre approximation of a probability density from discrete data

Abstract
We produce a positive approximation of a probability density in [0,1] when only a finite number of values (possibly affected by noise) is available. This approximation is obtained by computing a number of Legendre-Fourier coefficients and applying the Maximum Entropy method. An example of application of this procedure is data-smoothing in the numerical solution of an identification problem for Fokker-Planck equation.
Anno
2003
Tipo pubblicazione
Altri Autori
Inglese G.
Editore
Koninklijke Vlaamse Ingenieursvereniging
Rivista
Journal of computational and applied mathematics