A continuation multilevel Monte Carlo algorithm

Verfasser / Beitragende:
[Nathan Collier, Abdul-Lateef Haji-Ali, Fabio Nobile, Erik von Schwerin, Raúl Tempone]
Ort, Verlag, Jahr:
2015
Enthalten in:
BIT Numerical Mathematics, 55/2(2015-06-01), 399-432
Format:
Artikel (online)
ID: 605497141
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024 7 0 |a 10.1007/s10543-014-0511-3  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s10543-014-0511-3 
245 0 2 |a A continuation multilevel Monte Carlo algorithm  |h [Elektronische Daten]  |c [Nathan Collier, Abdul-Lateef Haji-Ali, Fabio Nobile, Erik von Schwerin, Raúl Tempone] 
520 3 |a We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. The actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients. 
540 |a Springer Science+Business Media Dordrecht, 2014 
690 7 |a Multilevel Monte Carlo  |2 nationallicence 
690 7 |a Monte Carlo  |2 nationallicence 
690 7 |a Partial differential equations with random data  |2 nationallicence 
690 7 |a Stochastic differential equations  |2 nationallicence 
690 7 |a Bayesian inference  |2 nationallicence 
700 1 |a Collier  |D Nathan  |u Environmental Sciences Division, Oak Ridge National Lab, Climate Change Science Institute (CCSI), Oak Ridge, USA  |4 aut 
700 1 |a Haji-Ali  |D Abdul-Lateef  |u Applied Mathematics and Computational Sciences, KAUST, Thuwal, Saudi Arabia  |4 aut 
700 1 |a Nobile  |D Fabio  |u MATHICSE-CSQI, EPF de Lausanne, Lausanne, Switzerland  |4 aut 
700 1 |a von Schwerin  |D Erik  |u Department of Mathematics, Kungliga Tekniska Högskolan, 100 44, Stockholm, Sweden  |4 aut 
700 1 |a Tempone  |D Raúl  |u Applied Mathematics and Computational Sciences, KAUST, Thuwal, Saudi Arabia  |4 aut 
773 0 |t BIT Numerical Mathematics  |d Springer Netherlands  |g 55/2(2015-06-01), 399-432  |x 0006-3835  |q 55:2<399  |1 2015  |2 55  |o 10543 
856 4 0 |u https://doi.org/10.1007/s10543-014-0511-3  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s10543-014-0511-3  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Collier  |D Nathan  |u Environmental Sciences Division, Oak Ridge National Lab, Climate Change Science Institute (CCSI), Oak Ridge, USA  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Haji-Ali  |D Abdul-Lateef  |u Applied Mathematics and Computational Sciences, KAUST, Thuwal, Saudi Arabia  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Nobile  |D Fabio  |u MATHICSE-CSQI, EPF de Lausanne, Lausanne, Switzerland  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a von Schwerin  |D Erik  |u Department of Mathematics, Kungliga Tekniska Högskolan, 100 44, Stockholm, Sweden  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Tempone  |D Raúl  |u Applied Mathematics and Computational Sciences, KAUST, Thuwal, Saudi Arabia  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t BIT Numerical Mathematics  |d Springer Netherlands  |g 55/2(2015-06-01), 399-432  |x 0006-3835  |q 55:2<399  |1 2015  |2 55  |o 10543