The asymptotic behavior of quadratic forms in heavy-tailed strongly dependent random variables
Suppose that Xt = [summation operator][infinity]j=0cjZt-j is a stationary linear sequence with regularly varying cj's and with innovations {Zj} that have infinite variance. Such a sequence can exhibit both high variability and strong dependence. The quadratic form 89 plays an important role in the estimation of the intensity of strong dependence. In contrast with the finite variance case, n-1/2(Qn - EQn) does not converge to a Gaussian distribution. We provide conditions on the cj's and on \gh for the quadratic form Qn, adequately normalized and randomly centered, to converge to a stable law of index [alpha], 1 < [alpha] < 2, as n tends to infinity.
Year of publication: |
1997
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Authors: | Kokoszka, Piotr S. ; Taqqu, Murad S. |
Published in: |
Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 66.1997, 1, p. 21-40
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Publisher: |
Elsevier |
Subject: | 60F05 60E07 |
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