Some strong limit theorems for weighted product sums of -mixing sequences of random variables.
Wu, Qunying, Jiang, Yuanying (2009)
Journal of Inequalities and Applications [electronic only]
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Displaying similar documents to “Convergence of weighted linear process for -mixing random variables.”
Some strong limit theorems for weighted product sums of -mixing sequences of random variables.
Strong law of large numbers for -mixing sequences with different distributions.
Cai, Guang-Hui (2006)
Discrete Dynamics in Nature and Society
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Random sums of random vectors and multitype families of productive individuals.
Rahimov, I., Muttlak, H. (2004)
International Journal of Mathematics and Mathematical Sciences
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An invariance principle for LPQD random variables.
Oliveira, P.E., Suquet, Ch. (1996)
Portugaliae Mathematica
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Asymptotics of Bernoulli random walks, bridges, excursions and meanders with a given number of peaks.
Labarbe, Jean-Maxime, Marckert, Jean-Francois (2007)
Electronic Journal of Probability [electronic only]
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Exponential inequalities and functional central limit theorems for random fields
Jérôme Dedecker (2001)
ESAIM: Probability and Statistics
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We establish new exponential inequalities for partial sums of random fields. Next, using classical chaining arguments, we give sufficient conditions for partial sum processes indexed by large classes of sets to converge to a set-indexed brownian motion. For stationary fields of bounded random variables, the condition is expressed in terms of a series of conditional expectations. For non-uniform -mixing random fields, we require both finite fourth moments and an algebraic decay of the...
Invariance principles in Hölder spaces.
Hamadouche, D. (2000)
Portugaliae Mathematica
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The notion of -weak dependence and its applications to bootstrapping time series.
Doukhan, Paul, Neumann, Michael H. (2008)
Probability Surveys [electronic only]
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Complete convergence for weighted sums of -mixing random variables.
Sung, Soo Hak (2010)
Discrete Dynamics in Nature and Society
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Adaptive estimation of the stationary density of discrete and continuous time mixing processes
Fabienne Comte, Florence Merlevède (2002)
ESAIM: Probability and Statistics
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In this paper, we study the problem of non parametric estimation of the stationary marginal density of an or a -mixing process, observed either in continuous time or in discrete time. We present an unified framework allowing to deal with many different cases. We consider a collection of finite dimensional linear regular spaces. We estimate using a projection estimator built on a data driven selected linear space among the collection. This data driven choice is performed via the...
Recent advances in invariance principles for stationary sequences.
Merlevède, Florence, Peligrad, Magda, Utev, Sergey (2006)
Probability Surveys [electronic only]
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