Artículo
Central limit theorem for a class of globally correlated random variables
Fecha de publicación:
06/2016
Editorial:
American Physical Society
Revista:
Physical Review E
ISSN:
2470-0053
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The standard central limit theorem with a Gaussian attractor for the sum of independent random variables may lose its validity in the presence of strong correlations between the added random contributions. Here, we study this problem for similar interchangeable globally correlated random variables. Under these conditions, a hierarchical set of equations is derived for the conditional transition probabilities. This result allows us to define different classes of memory mechanisms that depend on a symmetric way on all involved variables. Depending on the correlation mechanisms and statistics of the single variables, the corresponding sums are characterized by distinct probability densities. For a class of urn models it is also possible to characterize their domain of attraction, which, as in the standard case, is parametrized by the probability density of each random variable. Symmetric and asymmetric q-Gaussian attractors (q<1) arise in a particular two-state case of these urn models.
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Articulos(CCT - PATAGONIA NORTE)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - PATAGONIA NORTE
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - PATAGONIA NORTE
Citación
Budini, Adrian Adolfo; Central limit theorem for a class of globally correlated random variables; American Physical Society; Physical Review E; 93; 6; 6-2016; 62114-62114
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