Aggregation of weakly dependent doubly stochastic processes

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dc.creatorFermin, Lisandro J.
dc.date2008-05-13
dc.date.accessioned2026-07-07T09:38:45Z
dc.date.available2026-07-07T09:38:45Z
dc.descriptionThe aim of this paper is to extend the aggregation convergence results given in (Dacunha-Castelle and Fermin 2005, Dacunha-Castelle and Fermin 2008) to doubly stochastic linear and nonlinear processes with weakly dependent innovations. First, we introduce a weak dependence notion for doubly stochastic processes, based in the weak dependence definition given in (Doukhan and Louhichi 1999), and we exhibe several models satisfying this notion, such as: doubly stochastic Volterra processes and doubly stochastic Bernoulli scheme with weakly dependent innovations. Afterwards we derive a central limit theorem for the partial aggregation sequence considering weakly dependent doubly stochastic processes. Finally, show a new SLLN for the covariance function of the partial aggregation process in the case of doubly stochastic Volterra processes with interactive innovations. Keywords: Aggregation, weak dependence, doubly stochastic processes, Volterra processes, Bernoulli shift, TCL, SLLN.
dc.description33 pages
dc.identifierhttps://arxiv.org/abs/0805.1949
dc.identifierhttp://arxiv.org/abs/0805.1949
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/160924
dc.subjectProbability
dc.subjectStatistics Theory
dc.subject60G10, 60F05, 60F15
dc.titleAggregation of weakly dependent doubly stochastic processes
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