Non-Gaussian Chi-squared method with the multivariate Edgeworth expansion

dc.creatorAmendola, Luca
dc.date1998-10-13
dc.date.accessioned2026-07-07T02:28:22Z
dc.date.available2026-07-07T02:28:22Z
dc.descriptionI present here a generalization of the maximum likelihood method and the $χ^2$ method to the cases in which the data are {\it not} assumed to be Gaussian distributed. The method, based on the multivariate Edgeworth expansion, can find several astrophysical applications. I mention only two of them. First, in the microwave background analysis, where it cannot be excluded that the initial perturbations are non-Gaussian. Second, in the large scale structure statistics, as we already know that the galaxy distribution deviates from Gaussianity on the scales at which non-linearity is important. As a first interesting result I show here how the confidence regions are modified when non-Gaussianity is taken into account.
dc.description7 pages, 2 figures. This is a paper published in 1996 in the proceedings of an Italian meeting. Since the proceedings are hard to find, and I got some requests for this work, I decided to put it on the web, in its original form (updating the references)
dc.identifierhttps://arxiv.org/abs/astro-ph/9810198
dc.identifierhttp://arxiv.org/abs/astro-ph/9810198
dc.identifierAstro. Lett. and Communications, 1996, 33, 63
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/13094
dc.subjectAstrophysics
dc.titleNon-Gaussian Chi-squared method with the multivariate Edgeworth expansion
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