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title:
Computing Quadrature Formulas for Marginal Distributions of SDEs |
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name:
Yaroslavtseva |
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first name:
Larisa
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location/conference:
SPP-JT12
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PRESENTATION-link:
http://www.dfg-spp1324.de/nuhagtools/event_NEW/dateien/SPP-JT12/talks/Yaroslavtseva-jt12.pdf |
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abstract:
We consider the problem of approximating the marginal distribution of the solution of a stochastic differential equation (SDE) by probability measures with finite support. We study deterministic algorithms in a worst case analysis with respect to classes of SDEs, which are defined in terms of smoothness constraints for the coefficients of the equation.
The cost of a single approximation is given by the total
computational effort to compute the corresponding nodes and weights. For the definition of the error of a single approximation we consider the resulting quadrature rule and employ its worst case quadrature error over a class of test functions.
We present and discuss sharp asymptotic bounds on the respective N-th minimal errors. |
