A Central Limit Theorem for Contractive Stochastic Dynamical Systems
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Publication:4393836
DOI10.1239/jap/1032192562zbMath0906.60051OpenAlexW1971948777MaRDI QIDQ4393836
Publication date: 31 January 1999
Published in: Journal of Applied Probability (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1239/jap/1032192562
Central limit and other weak theorems (60F05) Discrete-time Markov processes on general state spaces (60J05)
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Central limit theorems for iterated random Lipschitz mappings. ⋮ On null-homology and stationary sequences ⋮ Multidimensional renewal theory in the non-centered case: application to strongly ergodic Markov chains ⋮ Robustness of iterated function systems of Lipschitz maps ⋮ Convergence to stable laws for multidimensional stochastic recursions: the case of regular matrices ⋮ Asymptotics of stationary solutions of multivariate stochastic recursions with heavy tailed inputs and related limit theorems ⋮ Heavy tail phenomenon and convergence to stable laws for iterated Lipschitz maps ⋮ Stabilized model reduction for nonlinear dynamical systems through a contractivity-preserving framework ⋮ The Nagaev-Guivarc’h method via the Keller-Liverani theorem ⋮ Rate of convergence in the central limit theorem for strongly ergodic Markov chains ⋮ On the recurrence set of planar Markov random walks ⋮ A note on invariance principles for iterated random functions ⋮ Recurrence of two-dimensional queueing processes, and random walk exit times from the quadrant ⋮ Random iterations of maps on Rk : asymptotic stability, synchronisation and functional central limit theorem
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