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Harnack inequality and gradient estimate for G-SDEs with degenerate noise 被引量:1
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作者 Xing Huang Fen-Fen Yang 《Science China Mathematics》 SCIE CSCD 2022年第4期813-826,共14页
In this paper,the Harnack inequality for G-SDEs with degenerate noise is derived by the method of coupling by change of the measure.Moreover,for any bounded and continuous function f,the gradient estimate∣∇P_(t)f∣≤... In this paper,the Harnack inequality for G-SDEs with degenerate noise is derived by the method of coupling by change of the measure.Moreover,for any bounded and continuous function f,the gradient estimate∣∇P_(t)f∣≤c(p,t)(Pt|f|p)^(1/p),p>1,t>0 is obtained for the associated nonlinear semigroup P¯t.As an application of the Harnack inequality,we prove the existence of the weak solution to degenerate G-SDEs under some integrable condition.Finally,an example is presented.All of the above results extend the existing ones in the linear expectation setting. 展开更多
关键词 Harnack inequality degenerate noise g-sde gradient estimate weak solution invariant expectation
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Harnack inequality and gradient estimate for functional G-SDEs with degenerate noise
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作者 Fen-Fen Yang 《Probability, Uncertainty and Quantitative Risk》 2022年第2期119-132,共14页
In this paper,the Harnack and shift Harnack inequalities for functional G-SDEs with degenerate noise are derived by the method of coupling by change of measure.Moreover,the gradient estimate for the associated nonline... In this paper,the Harnack and shift Harnack inequalities for functional G-SDEs with degenerate noise are derived by the method of coupling by change of measure.Moreover,the gradient estimate for the associated nonlinear semigroup P_(t) is obtained.All of the above results extend the existed results in linear expectation setting. 展开更多
关键词 Harnack inequality Gradient estimate Degenerate noise Functional g-sdes
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分布不确定下随机微分方程参数最小二乘估计 被引量:2
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作者 费晨 费为银 《数学物理学报(A辑)》 CSCD 北大核心 2019年第6期1499-1513,共15页
在分布不确定性条件下,基于离散观察数据,研究了随机微分方程(SDE)参数最小二乘估计(LSE)的相合性,其中噪声特征为G-布朗运动.为了得到参数估计相合性的主要结果,利用次线性期望的随机微积分理论,给出了一些引理.结果表明,在一定的正则... 在分布不确定性条件下,基于离散观察数据,研究了随机微分方程(SDE)参数最小二乘估计(LSE)的相合性,其中噪声特征为G-布朗运动.为了得到参数估计相合性的主要结果,利用次线性期望的随机微积分理论,给出了一些引理.结果表明,在一定的正则性条件下,基于分布不确定的最小二乘估计具有强相合性.最后,给出了一个算例说明理论的有效性. 展开更多
关键词 G-随机微分方程(g-sde) 次线性期望 最小二乘估计量 容度的指数鞅不等式 强相合性
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单调性条件下G-Brown运动驱动的倒向随机微分方程 被引量:2
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作者 宋阳 《数学年刊(A辑)》 CSCD 北大核心 2019年第2期177-198,共22页
研究了由G-Brown运动驱动的倒向随机微分方程■解的存在唯一性问题.其生成元f关于z是Lipschitz连续的,关于y是线性增长且满足单调性条件.
关键词 G-Brown运动 倒向随机微分方程 单调性条件
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Numerical Scheme for Solving Stochastic Differential Equations with G-Lévy Process
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作者 Jiawen Mei Yifei Xin 《Journal of Applied Mathematics and Physics》 2022年第2期466-474,共9页
In this paper, we propose numerical schemes for stochastic differential equations driven by G-Lévy process under the G-expectation framework. By using G-It&#244;formula and G-expectation property, we propose ... In this paper, we propose numerical schemes for stochastic differential equations driven by G-Lévy process under the G-expectation framework. By using G-It&#244;formula and G-expectation property, we propose Euler scheme and Milstein scheme which have order-1.0 convergence rate. And two numerical experiments including Ornstein-Uhlenbeck and Black-Scholes cases are given. 展开更多
关键词 G-Lévy Process G-Expectation Property SDEs Euler Scheme
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Path independence of additive functionals for stochastic differential equations under G-framework 被引量:2
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作者 Panpan REN Fen-Fen YANG 《Frontiers of Mathematics in China》 SCIE CSCD 2019年第1期135-148,共14页
The path independence of additive functionals for stochastic differential equations (SDEs) driven by the G-Brownian motion is characterized by the nonlinear partial differential equations. The main result generalizes ... The path independence of additive functionals for stochastic differential equations (SDEs) driven by the G-Brownian motion is characterized by the nonlinear partial differential equations. The main result generalizes the existing ones for SDEs driven by the standard Brownian motion. 展开更多
关键词 Stochastic DIFFERENTIAL EQUATION (SDE) partial DIFFERENTIAL EQUATION (PDE) additive functional g-sdes G-Brownian motion nonlinear PDE
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