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A Note on the Importance of Weak Convergence Rates for SPDE Approximations in Multilevel Monte Carlo Schemes

Annika Lang (Institutionen för matematiska vetenskaper, matematisk statistik)
11th International Conference on Monte Carlo and Quasi Monte Carlo Methods in Scientific Computing, MCQMC 2014, Leuven, Belgium, 6-11 April 2014 (2194-1009). Vol. 163 (2016), p. 489-505.
[Konferensbidrag, refereegranskat]

It is a well-known rule of thumb that approximations of stochastic partial differential equations have essentially twice the order of weak convergence compared to the corresponding order of strong convergence. This is already known for many approximations of stochastic (ordinary) differential equations while it is recent research for stochastic partial differential equations. In this note it is shown how the availability of weak convergence results influences the number of samples in multilevel Monte Carlo schemes and therefore reduces the computational complexity of these schemes for a given accuracy of the approximations.


Denna post skapades 2015-10-01. Senast ändrad 2016-12-06.
CPL Pubid: 223545


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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)


Tillämpad matematik
Sannolikhetsteori och statistik

Chalmers infrastruktur