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.
Pathwise convergence of a n ovel numerical scheme based on semi-implicit method for stochastic differential-algebraic equation s with non-global lips- chitz coefficients
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A Taylor-based local linearization scheme for index-1 SDAEs achieves pathwise convergence of order 1/2 minus any positive epsilon under local Lipschitz and Khasminskii 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.
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Pathwise convergence of a linearization scheme for stochastic differential-algebraic equations under the local Lipschitz coefficients
A Taylor-based local linearization scheme for index-1 SDAEs achieves pathwise convergence of order 1/2 minus any positive epsilon under local Lipschitz and Khasminskii conditions.