Random bit quadrature and approximation of distributions on Hilbert spaces

DOI10.1007/s10208-018-9382-3zbMath1432.60044arXiv1707.05723OpenAlexW2963596125MaRDI QIDQ1727983

Klaus Ritter, Mario Hefter, Lukas Mayer, Michael B. Giles

Publication date: 21 February 2019

Published in: Foundations of Computational Mathematics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1707.05723

zbMATH Keywords

stochastic differential equationsquantizationintegrationmultilevel Monte Carlo algorithmsapproximation of probability measuresGaussian measures on Hilbert spacesrandom bits

Mathematics Subject Classification ID

Gaussian processes (60G15) Monte Carlo methods (65C05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical integration (65D30) Probability theory on linear topological spaces (60B11)

Related Items (9)

Asymptotics of one-dimensional Lévy approximations ⋮ Best finite constrained approximations of one-dimensional probabilities ⋮ Lower Bounds for the Number of Random Bits in Monte Carlo Algorithms ⋮ On the Power of Restricted Monte Carlo Algorithms ⋮ Wasserstein convergence rates for random bit approximations of continuous Markov processes ⋮ Uniform decomposition of probability measures: quantization, clustering and rate of convergence ⋮ A functional limit theorem for coin tossing Markov chains ⋮ Approximation rate in Wasserstein distance of probability measures on the real line by deterministic empirical measures ⋮ Analysis of Nested Multilevel Monte Carlo Using Approximate Normal Random Variables

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