English

A central limit theorem for stochastic recursive sequences of topical operators

Probability 2007-10-30 v3 Optimization and Control

Abstract

Let (An)nN(A_n)_{n\in\mathbb{N}} be a stationary sequence of topical (i.e., isotone and additively homogeneous) operators. Let x(n,x0)x(n,x_0) be defined by x(0,x0)=x0x(0,x_0)=x_0 and x(n+1,x0)=Anx(n,x0)x(n+1,x_0)=A_nx(n,x_0). It can model a wide range of systems including train or queuing networks, job-shop, timed digital circuits or parallel processing systems. When (An)nN(A_n)_{n\in\mathbb{N}} has the memory loss property, (x(n,x0))nN(x(n,x_0))_{n\in\mathbb{N}} satisfies a strong law of large numbers. We show that it also satisfies the CLT if (An)nN(A_n)_{n\in \mathbb{N}} fulfills the same mixing and integrability assumptions that ensure the CLT for a sum of real variables in the results by P. Billingsley and I. Ibragimov.

Keywords

Cite

@article{arxiv.math/0606668,
  title  = {A central limit theorem for stochastic recursive sequences of topical operators},
  author = {Glenn Merlet},
  journal= {arXiv preprint arXiv:math/0606668},
  year   = {2007}
}

Comments

Published at http://dx.doi.org/10.1214/105051607000000168 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)

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