Goodness-of-fit tests for multivariate stable distributions based on the empirical characteristic function
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Date
Authors
Meintanis, Simos G.
Ngatchou-Wandji, Joseph
Taufer, Emanuele
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
We consider goodness-of-fit testing for multivariate stable distributions. The proposed
test statistics exploit a characterizing property of the characteristic function of these
distributions and are consistent under some conditions. The asymptotic distribution is
derived under the null hypothesis as well as under local alternatives. Conditions for an
asymptotic null distribution free of parameters and for affine invariance are provided.
Computational issues are discussed in detail and simulations show that with proper choice
of the user parameters involved, the new tests lead to powerful omnibus procedures for
the problem at hand
Description
Citation
Meintanis, S.G. et al. 2015. Goodness-of-fit tests for multivariate stable distributions based on the empirical characteristic function. Journal of multivariate analysis, 140:171-192. [https://doi.org/10.1016/j.jmva.2015.05.006