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Stability analysis and classification of Runge–Kutta methods for index 1 stochastic differential-algebraic equations with scalar noise
Institution:1. Department of Mathematical Sciences, Norwegian University of Science and Technology, Norway;2. Universität zu Lübeck, Institut für Mathematik, Ratzeburger Allee 160, 23562 Lübeck, Germany;1. School of Mathematics and Statistics, Wuhan University, Wuhan 430000, PR China;2. School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, PR China;3. School of Mechanical and Electrical Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, PR China;1. Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0321, USA;2. Department of Veterinary Medicine, Wildlife Health Center, University of California, Davis, CA 95616, USA;1. IMUVA, Departamento de Matemática Aplicada, Universidad de Valladolid, Paseo de Belén, 7, 47011 Valladolid, Spain;2. IMUVA, Departamento de Matemáticas y Computación, Escuela Politécnica Superior, Universidad de Burgos, Avda. Cantabria, 09006 Burgos, Spain
Abstract:The problem of solving stochastic differential-algebraic equations (SDAEs) of index 1 with a scalar driving Wiener process is considered. Recently, the authors have proposed a class of stiffly accurate stochastic Runge–Kutta (SRK) methods that do not involve any pseudo-inverses or projectors for the numerical solution of the problem. Based on this class of approximation methods, classifications for the coefficients of stiffly accurate SRK methods attaining strong order 0.5 as well as strong order 1.0 are calculated. Further, the mean-square stability of the considered class of SRK methods is analyzed. As the main result, families of A-stable efficient order 0.5 and 1.0 stiffly accurate SRK methods with a minimal number of stages for SDEs as well as for SDAEs are presented.
Keywords:Stochastic differential-algebraic equation  Stochastic Runge–Kutta method  Classification  Mean-square stability
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