Gram Charlier and Edgeworth expansion for sample variance
Benhamou, Eric (2018), Gram Charlier and Edgeworth expansion for sample variance, Theoretical Mathematics and Applications, 8, 4, p. 17-31
TypeArticle accepté pour publication ou publié
Journal nameTheoretical Mathematics and Applications
MetadataShow full item record
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)In this paper, we derive a valid Edgeworth expansions for the Bessel corrected empirical variance when data are generated by a strongly mixing process whose distribution can be arbitrarily. The constraint of strongly mixing process makes the problem not easy. Indeed, even for a strongly mixing normal process, the distribution is unknown. Here, we do not assume any other assumption than a sufficiently fast decrease of the underlying distribution to make the Edgeworth expansion convergent. This results can obviously apply to strongly mixing normal process and provide an alternative to the work of Moschopoulos (1985) and Mathai (1982).
Subjects / Keywordssample variance; Edgeworth expansion
Showing items related by title and author.
Constantin, Camelia; du Mouza, Cedric; Litwin, Witold; Rigaux, Philippe; Schwarz, Thomas (2016) Article accepté pour publication ou publié