Quantitative Breuer-Major Theorems

Abstract

We consider sequences of random variables of the type S n = n −1/2 n k=1 { f (Gaussian process and f : R d → R is a measurable function. It is known that, under certain conditions on f and the covariance function r of X , S n converges in distribution to a normal variable S. In the present paper we derive several explicit upper bounds for quantities of the type |E[h(S n )] − E[h(S)]|, where h is a sufficiently smooth test function. Our methods are based on Malliavin calculus, on interpolation techniques and on the Stein's method for normal approximation. The bounds deduced in our paper depend only on Var[ f (X 1 )] and on simple infinite series involving the components of r . In particular, our results generalize and refine some classic CLTs given by Breuer and Major, Giraitis and Surgailis, and Arcones, concerning the normal approximation of partial sums associated with Gaussiansubordinated time series.