The Annals of Probability

Long-range dependence and Appell rank

Donatas Surgailis

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Abstract

We study limit distributions of sums $S_N^{(G)} = \sum_{t=1}^N G(X_t)$ of nonlinear functions $G(x)$ in stationary variables of the form $X_t = Y_t + Z_t$, where ${Y_t}$ is a linear (moving average) sequence with long-range dependence, and ${Z_ t}$ is a (nonlinear) weakly dependent sequence. In particular, we consider the case when ${Y_ t}$ is Gaussian and either (1)${Z_t}$ is a weakly dependent multilinear form in Gaussian innovations, or (2) ${Z_t}$ is a finitely dependent functional in Gaussian innovations or (3)${Z_t}$ is weakly dependent and independent of $Y_t$ . We show in all three cases that the limit distribution of $S^(G)_N$ is determined by the Appell rank of $G( x)$, or the lowest $k\geq 0$ such that $a_k = \partial^k E\{G(X_0+c)\}/\partial c^k|_{c=0 \not= 0$.

Article information

Source
Ann. Probab., Volume 28, Number 1 (2000), 478-497.

Dates
First available in Project Euclid: 18 April 2002

Permanent link to this document
https://projecteuclid.org/euclid.aop/1019160127

Digital Object Identifier
doi:10.1214/aop/1019160127

Mathematical Reviews number (MathSciNet)
MR1756013

Zentralblatt MATH identifier
1130.60306

Subjects
Primary: 60F05: Central limit and other weak theorems
Secondary: 60G15: Gaussian processes 62M10: Time series, auto-correlation, regression, etc. [See also 91B84]

Keywords
Long-range dependence noncentral limit theorems reduction principle Appell polynomials Appell rank

Citation

Surgailis, Donatas. Long-range dependence and Appell rank. Ann. Probab. 28 (2000), no. 1, 478--497. doi:10.1214/aop/1019160127. https://projecteuclid.org/euclid.aop/1019160127


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