Wiener integrals, Malliavin calculus and covariance measure structure
Wiener integrals, Malliavin calculus and covariance measure structure
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DOI：
10.1016/j.jfa.2007.03.031
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发表时间：
2006-06
影响因子：
1.7
通讯作者：
Ida Kruk;F. Russo;C. Tudor
中科院分区：
文献类型：
--
作者：
Ida Kruk;F. Russo;C. Tudor
引入了平方可积随机过程的协方差测度结构的概念。我们定义了Wiener积分，发展了一种适用于随机变分的形式，并仅在必要时作了高斯假设。我们的主要例子是具有平稳增量的有限二次变分过程和分叉布朗运动。
We introduce the notion of covariance measure structure for square integrable stochastic processes. We define Wiener integral, we develop a suitable formalism for stochastic calculus of variations and we make Gaussian assumptions only when necessary. Our main examples are finite quadratic variation processes with stationary increments and the bifractional Brownian motion.