The linear Steklov method for SDEs with non-globally Lipschitz coefficients: Strong convergence and simulation

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3 Citas (Scopus)

Resumen

We present an explicit numerical method for solving stochastic differential equations with non-globally Lipschitz coefficients. A linear version of the Steklov average under a split-step formulation supports our new solver. The linear Steklov method converges strongly with a standard one-half order. Also, we present numerical evidence that the explicit linear Steklov reproduces almost surely stability solutions with high-accuracy for diverse application models even for stochastic differential systems with super-linear diffusion coefficients.
Idioma originalEspañol (México)
Páginas (desde-hasta)408
Número de páginas423
PublicaciónJournal of Computational and Applied Mathematics
Volumen309
DOI
EstadoAceptada/en prensa - ene 2017

Palabras clave

  • Explicit methods; Steklov average; Stochastic differential equations; Strong convergence

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