Previous article Next article Weak Approximation of Solutions of Systems of Stochastic Differential EquationsG. N. Mil’shteinG. N. Mil’shteinhttps://doi.org/10.1137/1130095PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] I. I. Gikhman and , A. V. Skorokhod, Stochastic Differential Equations, Springer, New York, 1972 0242.60003 CrossrefGoogle Scholar[2] G. N. Mil'shtein, Approximate integration of stochastic differential equations, Theory Prob. Appl., 19 (1974), 557–562 0314.60039 LinkGoogle Scholar[3] N. J. Rao, , J. D. Borwanker and , D. Ramkrishna, Numerical solution of Ito integral equations, SIAM J. Control, 12 (1974), 125–139 49:8109 0245.65063 LinkGoogle Scholar[4] N. N. Nikitin and , V. D. Razevig, Methods for the digital simulation of stochastic differential equations and an estimate of their errors, Ž. Vyčisl. Mat. i Mat. Fiz., 18 (1978), 106–117, 268, (In Russian.) 57:8046 Google Scholar[5] E. Platen, An approximation method for a class of Itô processes, Litovsk. Mat. Sb., 21 (1981), 121–133 82g:60083 0465.60055 Google Scholar[6] W. Rümelin, Numerical treatment of stochastic differential equations, SIAM J. Numer. Anal., 19 (1982), 604–613 10.1137/0719041 83i:60075 0496.65038 LinkGoogle Scholar[7] G. N. Mil'shtein, A method of second-order accuracy integration of stochastic differential equations, Theory Prob. Appl., 23 (1978), 396–401 0422.60048 LinkGoogle Scholar[8] R. Z. Khas'minskii, Stability of Systems of Differential Equations under Random Perturbations of their Parameters, Nauka, Moscow, 1969, (In Russian.) Google Scholar[9] Yu. V. Rakitskii, , S. M. Ustinov and , I. G. Chernorutskii, Numerical Methods of Solving Stiff Systems, Nauka, Moscow, 1979, (In Russian.) 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