Art

J-GLOBAL ID：201602216472710826   Reference number：16A0175164

On Random Variable Used in Weak Approximation of Stochastic Differential Equations

確率微分方程式の弱い近似で使用される確率変数について

Author (1)： SAITO YOSHIHIRO (岐阜聖徳学園大 経済情報)
Material： 日本応用数理学会論文誌  (Transactions of the Japan Society for Industrial and Applied Mathematics)
Volume： 25  Issue： 4  Page： 267-283  Publication year： Dec. 25, 2015 
JST Material Number： L1010A  ISSN： 0917-2246  Document type： Article
Article type： 短報  Country of issue： Japan (JPN)  Language： JAPANESE (JA)

Thesaurus term： *stochastic differential equation ,  *approximation method ,  *solution(mathematics) ,  normal distribution ,  asymptotic stability ,  *stability analysis ,  broken line approximation ,  random number generation
Semi thesaurus term： approximation method ,  random variable ,  weak solution ,  numerical experiment

JST classification (1)： Fluctuation phenomena,random process,Brownian motion,and transport process  (BA08020B)

Reference (17)：

• Bruti-Liberati, N., Martini, F., Piccardi, M. and Platen, E., A hardware generator of multi-point distributed random numbers for Monte Carlo simulation, Math. Comput. Simulation, 77 (2008), 45-56.
• Bryden, A. and Higham, D. J., On the boundedness of asymptotic stability regions for the stochastic theta method, BIT Numerical Mathematics, 43 (2003), 1-6.
• 伏見正則, 乱数, 東京大学出版会, 東京, 1989.
• Greiner, A., Strittmatter, W., and Honerkamp, J., Numerical integration of stochastic differential equations, J. Statist. Physics, 51(1987), 95-108.
• Higham, D. J., Mean-square and asymptotic stability of the stochastic theta method, SIAM J. Numer. Anal., 38(2000), 753-769.

Terms in the title (3)： 確率微分方程式 ,  近似 ,  確率変数