Maximal Inequalities and an Invariance Principle for a Class of Weakly Dependent Random Variables

Sergey Utev and Magda Peligrad ()
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Sergey Utev: University of Nottingham
Magda Peligrad: University of Cincinnati

Journal of Theoretical Probability, 2003, vol. 16, issue 1, 101-115

Abstract: Abstract The aim of this paper is to investigate the properties of the maximum of partial sums for a class of weakly dependent random variables which includes the instantaneous filters of a Gaussian sequence having a positive continuous spectral density. The results are used to obtain an invariance principle for strongly mixing sequences of random variables in the absence of stationarity or strong mixing rates. An additional condition is imposed to the coefficients of interlaced mixing. The results are applied to linear processes of strongly mixing sequences.

Keywords: Maximal inequalities; invariance principles; dependent random variables; Rosenthal inequality (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (6)

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DOI: 10.1023/A:1022278404634

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