Stochastic theta methods for SDAEs with time-dependent singular matrices are shown to be well-posed, constraint-preserving, and weakly convergent of order one under global Lipschitz and linear growth assumptions.
Strong convergence rate s of stochastic theta methods for index 1 stochastic differential algebraic equations under non-g lobally Lipschitz conditions
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Weak order one convergence of structure-preserving stochastic theta methods for stochastic differential algebraic equations with time-dependent singular matrices
Stochastic theta methods for SDAEs with time-dependent singular matrices are shown to be well-posed, constraint-preserving, and weakly convergent of order one under global Lipschitz and linear growth assumptions.