| Autor: |
Frances Y. Kuo, Ian H. Sloan, Michael B. Giles |
| Přispěvatelé: |
Owen, A, Glynn, P |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
Springer Proceedings in Mathematics & Statistics ISBN: 9783319914350 |
| Popis: |
Building on previous research which generalized multilevel Monte Carlo methods using either sparse grids or Quasi-Monte Carlo methods, this paper considers the combination of all these ideas applied to elliptic PDEs with finite-dimensional uncertainty in the coefficients. It shows the potential for the computational cost to achieve an \(O(\varepsilon )\) r.m.s. accuracy to be \(O(\varepsilon ^{-r})\) with \(r\! |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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