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Título
On the MS-stability of predictor–corrector schemes for stochastic differential equations
Autor(es)
Materia
Stochastic scheme
Predictor–corrector schemes
Mean-square stability
Multiplicative noise
Clasificación UNESCO
12 Matemáticas
Fecha de publicación
2021
Editor
Elsevier
Citación
Tocino, A., Zeghdane, R., Senosiaín, M.J. (2021). On the MS-stability of predictor–corrector schemes for stochastic differential equations. Mathematics and Computers in Simulation, 180, pp. 289-305.
Resumen
[EN] Predictor–corrector schemes are designed to be a compromise to retain the stability properties of the implicit schemes and the computational efficiency of the explicit ones. In this paper a complete analytical study for the linear mean-square stability of the two-parameter family of Euler predictor–corrector schemes for scalar stochastic differential equations is given. The analyzed family is given in terms of two parameters that control the degree of implicitness of the method. For each selection of the parameters the stability region is obtained, letting its comparison. Particular cases of the counter-intuitive fact of losing
numerical stability by reducing the step size, is confirmed and proved. Figures of the MS-stability regions and numerical examples that confirm the theoretical results are shown.
URI
ISSN
0378-4754
DOI
10.1016/j.matcom.2020.09.004
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