Approximation of an Integral Markov Process Arising in the Approximation of Stochastic Differential Equation
Approximation of an Integral Markov Process Arising in the Approximation of Stochastic Differential Equation作者机构：Department of Mathematics & Statistics University of North Florida Jacksonville FL-32224 USA
出 版 物：《Advances in Pure Mathematics》 (理论数学进展（英文）)
年 卷 期：2022年第12卷第1期
页 面：29-47页
学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学]
主 题：Variance Markov Process Parametric Noise Differential Equation Approximations
摘 要：We provide the derivation of a new formula for the approximation of an integral Markov process arising in the approximation of stochastic differential equations. This formula extends an existing formula derived in [1]. We have shown numerically that the leading order approximation of the differential equation with noise by solving an associated averaged problem and estimating the difference between them and the result is illustrated through some examples.
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