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A Central Limit Theorem for the Empirical Process of a Long Memory Linear Sequence

Giraitis, Liudas ; Surgailis, Donatas

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A central limit theorem for the normalized empirical process, basedon a (non-Gaussian) moving average sequence X_t , t in Z, with long memory,is established, generalizing the results of Dehling and Taqqu (1989). The proof is based on the (Appell) expansion 1(X_t <= x) = F(x) + f(x) X_t + ...of the indicator function, where F(x) = P[X_t <= x] is the marginaldistribution function, f(x) = F'(x), and the covariance of the remainder termdecays faster than the covariance of X_t. As a consequence, the limitdistribution of M-functionals and U-statistics based on such long memoryobservations is obtained.

Item Type: Working paper
Place of Publication: Heidelberg
Date Deposited: 13 Jun 2016 09:05
Date: December 1994
Number of Pages: 14
Faculties / Institutes: The Faculty of Mathematics and Computer Science > Department of Applied Mathematics
Subjects: 510 Mathematics
Schriftenreihe ID: Beiträge zur Statistik > Beiträge
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