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.
Goodness-of-fit tests for multivariate stable distributions based on the empirical characteristic function / Meintanis, Simos G.; Ngatchou Wandji, Joseph; Taufer, Emanuele. - In: JOURNAL OF MULTIVARIATE ANALYSIS. - ISSN 0047-259X. - STAMPA. - 140:(2015), pp. 171-192. [10.1016/j.jmva.2015.05.006]
Goodness-of-fit tests for multivariate stable distributions based on the empirical characteristic function
Taufer, Emanuele
2015-01-01
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.File | Dimensione | Formato | |
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2015 - JMVA - Gof tests for MV stable distributions based on the ECF.pdf
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