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Weak Convergence of the Sequential Empirical Process of some Long-Range Dependent Sequences with Respect to a Weighted Norm (1312.5894v2)

Published 20 Dec 2013 in math.PR, math.ST, and stat.TH

Abstract: Let $(X_k){k\geq1}$ be a Gaussian long-range dependent process with $EX_1=0$, $EX_12=1$ and covariance function $r(k)=k{-D}L(k)$. For any measurable function $G$ let $(Y_k){k\geq1}=(G(X_k))_{k\geq1}$. We study the asymptotic behaviour of the associated sequential empirical process $\left(R_N(x,t)\right)$ with respect to a weighted norm $|\cdot|_w$. We show that, after an appropriate normalization, $\left(R_N(x,t)\right)$ converges weakly in the space of c`adl`ag functions with finite weighted norm to a Hermite process.

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