Displaying similar documents to “Stochastic two-scale convergence in the mean and applications.”

Asymptotic normality of randomly truncated stochastic algorithms

Jérôme Lelong (2013)

ESAIM: Probability and Statistics

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We study the convergence rate of randomly truncated stochastic algorithms, which consist in the truncation of the standard Robbins–Monro procedure on an increasing sequence of compact sets. Such a truncation is often required in practice to ensure convergence when standard algorithms fail because the expected-value function grows too fast. In this work, we give a self contained proof of a central limit theorem for this algorithm under local assumptions on the expected-value function,...

Stability of stochastic differential equations driven by general semimartingales

Słomiński Leszek

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CONTENTS Introduction........................................................................................................5 0. Announcement of results...............................................................................7 1. Condition (UT).............................................................................................18 2. Weak convergence of solutions...................................................................26 ...

Large deviations, central limit theorems and L convergence for Young measures and stochastic homogenizations

Julien Michel, Didier Piau (2010)

ESAIM: Probability and Statistics

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We study the stochastic homogenization processes considered by Baldi (1988) and by Facchinetti and Russo (1983). We precise the speed of convergence towards the homogenized state by proving the following results: (i) a large deviations principle holds for the Young measures; if the Young measures are evaluated on a given function, then (ii) the speed of convergence is bounded in every L norm by an explicit rate and (iii) central limit theorems hold. In dimension 1, we apply these...