Numerical Methods for SDEs
Euler–Maruyama, Milstein, and weak/strong convergence.
Numerical Methods for SDEs. Euler–Maruyama, Milstein, and weak/strong convergence.
Foundations and canonical references
The standard treatments of numerical methods for sdes approach the subject from complementary angles. Kloeden, Numerical Solution of Stochastic Differential Equations (1992) is the anchor reference for the subject and lays out the core definitions, theorems, and worked examples that practitioners return to.
Open methodological questions for numerical methods for sdes include sharpening the bridges between foundational theory and computational practice, extending classical results to broader or more structured settings, and integrating the techniques surveyed above with adjacent mathematical disciplines. The references listed in this page are the entry points that current work builds on.
Prerequisites
Sources
- textbook · primary · 1992Numerical Solution of Stochastic Differential Equationskloeden-1992, platen-1992
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