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Gaussian Approximations of Multiple Integrals

  
@article{ECP1322,
	author = {Giovanni Peccati},
	title = {Gaussian Approximations of Multiple Integrals},
	journal = {Electron. Commun. Probab.},
	fjournal = {Electronic Communications in Probability},
	volume = {12},
	year = {2007},
	keywords = {Gaussian processes; Malliavin calculus; Multiple stochastic integrals; Non-central limit theorems; Weak convergence},
	abstract = {Fix $k\geq 1$, and let $I(l), l \geq 1$, be a sequence of $k$-dimensional vectors of multiple Wiener-Itô integrals with respect to a general Gaussian process. We establish necessary and sufficient conditions to have that, as $l \to\infty$, the law of $I(l)$ is asymptotically close (for example, in the sense of Prokhorov's distance) to the law of a $k$-dimensional Gaussian vector having the same covariance matrix as $I(l)$. The main feature of our results is that they require minimal assumptions (basically, boundedness of variances) on the asymptotic behaviour of the variances and covariances of the elements of $I(l)$. In particular, we will not assume that the covariance matrix of $I(l)$ is convergent. This generalizes the results proved in Nualart and Peccati (2005), Peccati and Tudor (2005) and Nualart and Ortiz-Latorre (2007). As shown in Marinucci and Peccati (2007b), the criteria established in this paper are crucial in the study of the high-frequency behaviour of stationary fields defined on homogeneous spaces.},
	pages = {no. 34, 350-364},
	issn = {1083-589X},
	doi = {10.1214/ECP.v12-1322},    
        url = {http://ecp.ejpecp.org/article/view/1322}}