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Sur les modèles Tweedie multivariés

Abstract : After a reminder of the natural exponential families framework and the univariate Tweedie distributions, we build two multivariate extension of the latter. A first construction, called Tweedie random vector, gives a multivariate Tweedie distribution parametrized by a mean vector and a dispersion matrix. We show that the correlations between the margins can be controlled and vary between -1 and 1. Some properties shared with the well-known Gaussian vector are given. By giving a matrix representation, we can simulate observations of Tweedie random vectors. The second construction establishes the multiple stable Tweedie models. They are vectors of which the first component is Tweedie and the others are independant Tweedie, given the first one, and with dispersion parameter given by an observation of the first component. We give the generalized variance and show that it is a product of powered component of the mean and give an efficient estimator of this parameter. Finally, we can show, with some restrictions, that the generalized variance is a tool which can be used for characterizing the natural exponential families generated by multiple stable Tweedie models.
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Submitted on : Wednesday, March 22, 2017 - 4:45:07 PM
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  • HAL Id : tel-01494103, version 1



Johann Cuenin. Sur les modèles Tweedie multivariés. Statistiques [math.ST]. Université de Franche-Comté, 2016. Français. ⟨NNT : 2016BESA2026⟩. ⟨tel-01494103⟩



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