The paper introduces improved stochastic ϑ-methods for the numerical integration of stochastic Volterra integral equations. Such methods, compared to those introduced by the authors in Conte et al. (2018)[14], have better stability properties. This is here made possible by inheriting the stability properties of the corresponding methods for systems of stochastic differential equations. Such a superiority is confirmed by a comparison of the stability regions.
Improved ϑ-methods for stochastic Volterra integral equations
Dajana Conte;Beatrice Paternoster
2021
Abstract
The paper introduces improved stochastic ϑ-methods for the numerical integration of stochastic Volterra integral equations. Such methods, compared to those introduced by the authors in Conte et al. (2018)[14], have better stability properties. This is here made possible by inheriting the stability properties of the corresponding methods for systems of stochastic differential equations. Such a superiority is confirmed by a comparison of the stability regions.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
2021 POST PRINT Improved theta-methods for stochastic Volterra integral equations, Comm. Nonlin. Sci. Numer. Simul. 93, article number 105528 (2021).pdf
Open Access dal 01/01/2024
Tipologia:
Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza:
DRM non definito
Dimensione
167.46 kB
Formato
Adobe PDF
|
167.46 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
