Lower and upper bounds for strong approximation errors for numerical approximations of stochastic heat equations
Work
Year: 2020
Type: article
Source: BIT Numerical Mathematics
Institutions ETH Zurich, Max Planck Institute for Mathematics in the Sciences, Max Planck Institute for Mathematics, Goethe University Frankfurt
Cites: 25
Cited by: 8
Related to: 10
FWCI: 0.871
Citation percentile (by year/subfield): 82.45
Subfield: Finance
Domain: Social Sciences
Open Access status: green