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Stochastic Processes and their Applications
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On linear processes with dependent innovations

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Abstract

We consider asymptotic behavior of partial sums and sample covariances for linear processes whose innovations are dependent. Central limit theorems and invariance principles are established under fairly mild conditions. Our results go beyond earlier ones by allowing a quite wide class of innovations which includes many important nonlinear time series models. Applications to linear processes with GARCH innovations and other nonlinear time series models are discussed. © 2005 Elsevier B.V. All rights reserved.

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Stochastic Processes and their Applications

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