Deterministic quadrature formulas for SDEs based on simplified weak Itô-Taylor steps

DOI10.1007/s10208-015-9277-5zbMath1382.65023OpenAlexW1190414567MaRDI QIDQ515988

Thomas Müller-Gronbach, Larisa Yaroslavtseva

Publication date: 17 March 2017

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

Full work available at URL: https://doi.org/10.1007/s10208-015-9277-5

zbMATH Keywords

stochastic differential equationconvergencenumerical examplelower boundsquadraturedeterministic algorithmoptimal algorithmssimplified weak Itô-Taylor step

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Ordinary differential equations and systems with randomness (34F05) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)

Related Items (8)

Evolution of the Viola-Jones Object Detection Method: A Survey ⋮ On non-polynomial lower error bounds for adaptive strong approximation of SDEs ⋮ Gauss-Quadrature Method for One-Dimensional Mean-Field SDEs ⋮ Convergence of the Euler-Maruyama method for multidimensional SDEs with discontinuous drift and degenerate diffusion coefficient ⋮ Truncated control variates for weak approximation schemes ⋮ On the complexity of computing quadrature formulas for marginal distributions of SDEs ⋮ Multilevel Monte Carlo for Stochastic Differential Equations with Small Noise ⋮ Constructive Quantization and Multilevel Algorithms for Quadrature of Stochastic Differential Equations

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