Gaussian Approximations for Non-stationary Multiple Time Series
نویسندگان
چکیده
We obtain an invariance principle for non-stationary vector-valued stochastic processes. It is shown that, under mild conditions, the partial sums of non-stationary processes can be approximated on a richer probability space by sums of independent Gaussian random vectors with nearly optimal bounds. The latter Gaussian approximation result has a wide range of applications in the study of multiple non-stationary time series.
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