An invariance principle for LPQD random variables.
Oliveira, P.E., Suquet, Ch. (1996)
Portugaliae Mathematica
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Displaying similar documents to “Invariance principles in Hölder spaces.”
An invariance principle for LPQD random variables.
Central limit theorem for sampled sums of dependent random variables
Nadine Guillotin-Plantard, Clémentine Prieur (2010)
ESAIM: Probability and Statistics
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We prove a central limit theorem for linear triangular arrays under weak dependence conditions. Our result is then applied to dependent random variables sampled by a -valued transient random walk. This extends the results obtained by [N. Guillotin-Plantard and D. Schneider, (2003) 477–497]. An application to parametric estimation by random sampling is also provided.
Weak convergence to the law of the brownian sheet
Maria Jolis (1988)
Annales scientifiques de l'Université de Clermont-Ferrand 2. Série Probabilités et applications
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On the strong laws for weighted sums of -mixing random variables.
Zhou, Xing-Cai, Tan, Chang-Chun, Lin, Jin-Guan (2011)
Journal of Inequalities and Applications [electronic only]
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An invariance principle in for non stationary -mixing sequences
Paulo Eduardo Oliveira, Charles Suquet (1995)
Commentationes Mathematicae Universitatis Carolinae
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Invariance principle in is studied using signed random measures. This approach to the problem uses an explicit isometry between and a reproducing kernel Hilbert space giving a very convenient setting for the study of compactness and convergence of the sequence of Donsker functions. As an application, we prove a version of the invariance principle in the case of -mixing random variables. Our result is not available in the -setting.
Limiting behaviour of moving average processes based on a sequence of mixing and negatively associated random variables.
Budsaba, Kamon, Chen, Pingyan, Volodin, Andrei (2007)
Lobachevskii Journal of Mathematics
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