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Part of the book series: Applications of Mathematics ((SMAP,volume 23))

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Abstract

In this chapter we shall propose and examine strong schemes which avoid the use of derivatives in much the same way that Runge-Kutta schemes do in the deterministic setting. We shall also call these Runge-Kutta schemes, but it must be emphasized that they are not simply heuristic generalizations of deterministic Runge-Kutta schemes to stochastic differential equations. The notation and abbreviations of the last chapter will continue to be used, often without direct reference.

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Bibliographical Notes

  • Clements, D. J. and B. D. O. Anderson (1973). Well behaved Ito equations with simulations that always misbehave. IEEE Trans. Automat. Control 18, 676–677.

    Article  MATH  Google Scholar 

  • Wright, D. J. (1974). The digital simulation of stochastic differential equations. IEEE Trans. Automat. Control 19, 75–76.

    Article  MATH  Google Scholar 

  • Rümelin, W. (1982). Numerical treatment of stochastic differential equations. SIAM J. Numer. Anal. 19 (3), 604–613.

    Article  MathSciNet  MATH  Google Scholar 

  • Smith, A. M. and C. W. Gardiner (1988). Simulation of nonlinear quantum damping using the positive representation. Univ. Waikato Research Report.

    Google Scholar 

  • Artemiev, S. S. (1993a). Certain aspects of application of numerical methods of solving SDE systems. In Numer. Anal.,Volume 1 of Bull. of the Novosibirsk Computing Center,pp. 1–16. NCC Publisher.

    Google Scholar 

  • Artemiev, S. S. (1993b). The stability of numerical methods for solving stochastic differential equations. In Numer. Anal.,Volume 2 of Bull. of the Novosibirsk Computing Center,pp. 1–10. NCC Publisher.

    Google Scholar 

  • Saito, Y. and T. Mitsui (1993b). T-stability of numerical schemes for stochastic differential equations. World Sci. Ser. Appl. Anal. 2, 333–344.

    MathSciNet  Google Scholar 

  • Burrage, K. and E. Platen (1994). Runge-Kutta methods for stochastic differential equations. Ann. Numer. Math. 1 (1–4), 63–78.

    MathSciNet  MATH  Google Scholar 

  • Komori, Y., Y. Saito, and T. Mitsui (1994). Some issues in discrete approximate solution for stochastic differential equations. Comput. Math. AppL 28 (10–12), 269–278.

    Article  MathSciNet  MATH  Google Scholar 

  • Komori, Y. and T. Mitsui (1995). Stable ROW-type weak scheme for stochastic differential equations. Monte Carlo Methods AppL 1 (4), 279–300.

    Article  MathSciNet  MATH  Google Scholar 

  • Saito, Y. and T. Mitsui (1996). Stability analysis of numerical schemes for stochastic differential equations. SIAM J. Numer. Anal. 33(6), 2254–2267.

    Google Scholar 

  • Burrage, K., P. M. Burrage, and J. A. Belward (1997). A bound on the maximum strong order of stochastic Runge-Kutta methods for stochastic ordinary differential equations. BIT 37 (4), 771–780.

    Article  MathSciNet  MATH  Google Scholar 

  • Burrage, K. and P. M. Burrage (1996). High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations. Appl. Numer. Math. 22, 81–101.

    Article  MathSciNet  MATH  Google Scholar 

  • Burrage, K. and P. M. Burrage (1997). General order conditions for stochastic RungeKutta methods for both commuting and non-commuting stochastic ordinary differential equation systems. Appl. Numer. Math. (to appear).

    Google Scholar 

  • Komori, Y., T. Mitsui, and H. Sugiura (1997). Rooted tree analysis of the order conditions of ROW-type scheme for stochastic differential equations. BIT 37(1) 43–66.

    Google Scholar 

  • Burrage, P. M. (1998). Runge-Kutta methods for stochastic differential equations. Ph. D. thesis, University of Queensland, Brisbane, Australia.

    Google Scholar 

  • Hofmann, N. and E. Platen (1994). Stability of weak numerical schemes for stochastic differential equations. Comput. Math. AppL 28(10–12), 45–57.

    Google Scholar 

  • Chang, C. C. (1987). Numerical solution of stochastic differential equations with constant diffusion coefficients. Math. Comp. 49, 523–542.

    Article  MathSciNet  MATH  Google Scholar 

  • Kloeden, P. E. and E. Platen (1992). Higher order implicit strong numerical schemes for stochastic differential equations. J. Statist. Phys. 66 (1/2), 283–314.

    Article  MathSciNet  MATH  Google Scholar 

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© 1992 Springer-Verlag Berlin Heidelberg

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Kloeden, P.E., Platen, E. (1992). Explicit Strong Approximations. In: Numerical Solution of Stochastic Differential Equations. Applications of Mathematics, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-12616-5_11

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  • DOI: https://doi.org/10.1007/978-3-662-12616-5_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-08107-1

  • Online ISBN: 978-3-662-12616-5

  • eBook Packages: Springer Book Archive

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