arXiv · 1605.06349
A Multilevel Approach towards Unbiased Sampling of Random Elliptic Partial Differential Equations
Abstract
Partial differential equation is a powerful tool to characterize various physics systems. In practice, measurement errors are often present and probability models are employed to account for such uncertainties. In this paper, we present a Monte Carlo scheme that yields unbiased estimators for expectations of random elliptic partial differential equations. This algorithm combines multilevel Monte Carlo [Giles, 2008] and a randomization scheme proposed by [Rhee and Glynn, 2012, Rhee and Glynn, 2013]. Furthermore, to obtain an estimator with both finite variance and finite expected computational cost, we employ higher order approximations.
Explore related subjects
Keep this discovery
Xiaoou Li, Jingchen Liu. 2016-05-20. A Multilevel Approach towards Unbiased Sampling of Random Elliptic Partial Differential Equations. https://arxiv.org/abs/1605.06349
Cite the original work for its findings. Save a collection to share your selection of sources.