
Abstract
To solve boundary value problems for linear systems of stochastic differential equations we propose and justify a numerical method based on the Gibbs sampler. In contrast to the technique which yields for linear systems an "exact" numerical solution, the proposed method is simpler to generalize for stochastic partial differential equations and nonlinear systems. Such generalizations are discussed as well.
Item Type: | Paper |
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Faculties: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
Subjects: | 500 Science > 510 Mathematics |
URN: | urn:nbn:de:bvb:19-epub-1707-2 |
Language: | English |
Item ID: | 1707 |
Date Deposited: | 10. Apr 2007 |
Last Modified: | 04. Nov 2020, 12:45 |