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Un teorema de convergencia con aplicación a la inferencia bayesiana.

Eusebio Gómez Sánchez-Manzano (1986)

Trabajos de Estadística

A theorem is proved showing that, assuming some boundary conditions, the following hypotheses:1. {Xn} is a sequence of continuous random variables which approaches in probability to a numerical sequence {an},2. {Yn} is another sequence of random variables such that, for all n, the density function of Yn is proportional to the product of the density of Xn by another density not depending on n,lead to the fact that the random sequence {Yn} also approaches in probability to {an}.We also show some related...

Universality for random tensors

Razvan Gurau (2014)

Annales de l'I.H.P. Probabilités et statistiques

We prove two universality results for random tensors of arbitrary rank D . We first prove that a random tensor whose entries are N D independent, identically distributed, complex random variables converges in distribution in the large N limit to the same limit as the distributional limit of a Gaussian tensor model. This generalizes the universality of random matrices to random tensors. We then prove a second, stronger, universality result. Under the weaker assumption that the joint probability distribution...

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