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arxiv: 1401.2247 · v1 · pith:ZBYMHOWVnew · submitted 2014-01-10 · 🧮 math.PR

Strong asymptotic independence on Wiener chaos

classification 🧮 math.PR
keywords asymptoticchaoseveryindependencerandomvectorswienerasymptotically
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Let $F_n = (F_{1,n}, ....,F_{d,n})$, $n\geq 1$, be a sequence of random vectors such that, for every $j=1,...,d$, the random variable $F_{j,n}$ belongs to a fixed Wiener chaos of a Gaussian field. We show that, as $n\to\infty$, the components of $F_n$ are asymptotically independent if and only if ${\rm Cov}(F_{i,n}^2,F_{j,n}^2)\to 0$ for every $i\neq j$. Our findings are based on a novel inequality for vectors of multiple Wiener-It\^o integrals, and represent a substantial refining of criteria for asymptotic independence in the sense of moments recently established by Nourdin and Rosinski.

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