Expansions for nearly Gaussian distributions

Free access article

Issue		Astron. Astrophys. Suppl. Ser. Volume 130, Number 1, May_II 1998


Page(s)		193 - 205
DOI		http://dx.doi.org/10.1051/aas:1998221

DOI: 10.1051/aas:1998221

Astron. Astrophys. Suppl. Ser. 130, 193-205

S. Blinnikov ^1,2 - R. Moessner ²

Send offprint request: S. Blinnikov

1 - Institute for Theoretical and Experimental Physics, 117259, Moscow, Russia
Sternberg Astronomical Institute, 119899 Moscow, Russia
2 - Max-Planck-Institut für Astrophysik, D-85740 Garching, Germany

Received July 8; accepted November 10, 1997

Abstract:

Various types of expansions in series of Chebyshev-Hermite polynomials currently used in astrophysics for weakly non-normal distributions are compared, namely the Gram-Charlier, Gauss-Hermite and Edgeworth expansions. It is shown that the Gram-Charlier series is most suspect because of its poor convergence properties. The Gauss-Hermite expansion is better but it has no intrinsic measure of accuracy. The best results are achieved with the asymptotic Edgeworth expansion. We draw attention to the form of this expansion found by Petrov for arbitrary order of the asymptotic parameter and present a simple algorithm realizing Petrov's prescription for the Edgeworth expansion. The results are illustrated by examples similar to the problems arising when fitting spectral line profiles of galaxies, supernovae, or other stars, and for the case of approximating the probability distribution of peculiar velocities in the cosmic string model of structure formation.

Key words: methods: statistical; cosmic strings; line: profiles

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