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arXiv math/0604527math.PR
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广义随机积分的稳定收敛性与条件原理:L^2理论

Stable convergence of generalized stochastic integrals and the principle of conditioning: L^2 theory

Giovanni Peccati, Murad S. Taqqu

摘要:

考虑具有二阶矩的独立离散随机测度的广义适应随机积分。我们使用解耦技术,被称为“原则的条件”,研究他们的稳定收敛到混合物的无穷可分分布。我们的结果适用于,特别是,多重积分的独立分散和平方可积〔的〕随机措施,以及Skorohod积分抽象的维纳空间。作为一个具体的应用,我们建立了关于一般Poisson测度的二重积分序列的中心极限定理,从而将Nualart和Peccati(2005)以及Peccati和Tudor(2004)中的结果推广到非高斯情形.

英文摘要:

Consider generalized adapted stochastic integrals with respect to independently scattered random measures with second moments. We use a decoupling technique, known as the "principle of conditioning", to study their stable convergence towards mixtures of infinitely divisible distributions. Our results apply, in particular, to multiple integrals with respect to independently scattered and square integrable random measures, as well as to Skorohod integrals on abstract Wiener spaces. As a specific application, we establish a Central Limit Theorem for sequences of double integrals with respect to a general Poisson measure, thus extending the results contained in Nualart and Peccati (2005) and Peccati and Tudor (2004) to a non-Gaussian context.

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