Weak convergence of the weighted sequential empirical process of some long-range dependent data

Let (Xk)k≥1 be a Gaussian long-range dependent process with EX1=0, EX12=1 and covariance function r(k)=k−DL(k). For any measurable function G let (Yk)k≥1=(G(Xk))k≥1. We study the asymptotic behaviour of the associated sequential empirical process (RN(x,t)) with respect to a weighted sup-norm ‖⋅‖w. We show that, after an appropriate normalization, (RN(x,t)) converges weakly in the space of cadlag functions with finite weighted norm to a Hermite process.