Gaussian limits for vector-valued multiple stochastic integrals
نویسندگان
چکیده
We establish necessary and sufficient conditions for a sequence of d-dimensional vectors of multiple stochastic integrals Fd = ` F k 1 , ..., F k d ́ , k ≥ 1, to converge in distribution to a d-dimensional Gaussian vector Nd = (N1, ..., Nd). In particular, we show that if the covariance structure of F k d converges to that of Nd, then componentwise convergence implies joint convergence. These results extend to the multidimensional case the main theorem of [9].
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