Convergence theorems for partial sums of arbitrary stochastic sequences.
Wang, Xiaosheng, Guo, Haiying (2010)
Journal of Inequalities and Applications [electronic only]
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Wang, Xiaosheng, Guo, Haiying (2010)
Journal of Inequalities and Applications [electronic only]
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Montgomery-Smith, Stephen (1998)
Electronic Journal of Probability [electronic only]
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Saejung, Satit, Gao, Ji (2010)
Abstract and Applied Analysis
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David Culpin (1980)
Aplikace matematiky
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Pierre Del Moral, Arnaud Doucet, Sumeetpal S. Singh (2010)
ESAIM: Mathematical Modelling and Numerical Analysis
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We design a particle interpretation of Feynman-Kac measures on path spaces based on a backward Markovian representation combined with a traditional mean field particle interpretation of the flow of their final time marginals. In contrast to traditional genealogical tree based models, these new particle algorithms can be used to compute normalized additive functionals “on-the-fly” as well as their limiting occupation measures with a given precision degree that does not depend on the...
Sanjoy Ghosal (2013)
Applications of Mathematics
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In this paper the ideas of three types of statistical convergence of a sequence of random variables, namely, statistical convergence in probability, statistical convergence in mean of order and statistical convergence in distribution are introduced and the interrelation among them is investigated. Also their certain basic properties are studied.