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We propose a new tamed Milstein-type scheme for stochastic differential equation with Markovian switching when drift coefficient is assumed to grow super-linearly. The strong rate of convergence is shown to be equal to $1.0$ under mild…

概率论 · 数学 2019-09-18 Chaman Kumar , Tejinder Kumar

In this paper a drift-randomized Milstein method is introduced for the numerical solution of non-autonomous stochastic differential equations with non-differentiable drift coefficient functions. Compared to standard Milstein-type methods we…

数值分析 · 数学 2018-12-12 Raphael Kruse , Yue Wu

We study the traditional backward Euler method for $m$-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H > 1/2$ whose drift coefficient satisfies the one-sided Lipschitz condition.…

数值分析 · 数学 2022-05-30 Hao Zhou , Yaozhong Hu , Yanghui Liu

This work presents a randomized-tamed Milstein scheme for stochastic differential equations whose drift coefficient exhibits superlinear growth in the state variable and limited temporal regularity, quantified by $\beta$-H\"older continuity…

数值分析 · 数学 2026-01-15 Sani Biswas

We propose an explicit drift-randomised Milstein scheme for both McKean--Vlasov stochastic differential equations and associated high-dimensional interacting particle systems with common noise. By using a drift-randomisation step in space…

概率论 · 数学 2023-06-19 Sani Biswas , Chaman Kumar , Neelima , Gonçalo dos Reis , Christoph Reisinger

A new explicit stochastic scheme of order 1 is proposed for solving commutative stochastic differential equations (SDEs) with non-globally Lipschitz continuous coefficients. The proposed method is a semi-tamed version of Milstein scheme to…

数值分析 · 数学 2021-10-13 Yulong Liu , Yuanling Niu , Xiujun Cheng

We consider a higher-order Milstein scheme for stochastic partial differential equations with trace class noise which fulfill a certain commutativity condition. A novel technique to generally improve the order of convergence of Taylor…

数值分析 · 数学 2018-08-15 Claudine Leonhard , Andreas Rößler

In this paper, we derive fully implementable first order time-stepping schemes for McKean--Vlasov stochastic differential equations (McKean--Vlasov SDEs), allowing for a drift term with super-linear growth in the state component. We propose…

概率论 · 数学 2021-04-28 Jianhai Bao , Christoph Reisinger , Panpan Ren , Wolfgang Stockinger

This paper focuses on two variants of the Milstein scheme, namely the split-step backward Milstein method and a newly proposed projected Milstein scheme, applied to stochastic differential equations which satisfy a global monotonicity…

数值分析 · 数学 2017-01-16 Wolf-Jürgen Beyn , Elena Isaak , Raphael Kruse

We survey recent developments in the field of complexity of pathwise approximation in $p$-th mean of the solution of a stochastic differential equation at the final time based on finitely many evaluations of the driving Brownian motion.…

概率论 · 数学 2024-03-04 T. Müller-Gronbach , L. Yaroslavtseva

An explicit Milstein-type scheme for stochastic differential equation with Markovian switching is derived and its strong convergence in $\mathcal{L}^2$-sense is established without using It\^o-Taylor expansion formula. Rate of strong…

概率论 · 数学 2019-09-18 Chaman Kumar , Tejinder Kumar

We introduce a semi-implicit Milstein approximation scheme for some class of non-colliding particle systems modeled by systems of stochastic differential equations with non-constant diffusion coefficients. We show that the scheme converges…

概率论 · 数学 2019-08-13 Hoang-Long Ngo , Duc-Trong Luong

In this paper, we study a class of one-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H>\ff 1 2$. The drift term of the equation is locally Lipschitz and unbounded in the…

概率论 · 数学 2019-01-01 Shao-Qin Zhang , Chenggui Yuan

We propose a new simple and explicit numerical scheme for time-homogeneous stochastic differential equations. The scheme is based on sampling increments at each time step from a skew-symmetric probability distribution, with the level of…

Higher order schemes for stochastic partial differential equations that do not possess commutative noise require the simulation of iterated stochastic integrals. In this work, we propose a derivative-free Milstein type scheme to approximate…

概率论 · 数学 2020-06-16 Claudine von Hallern , Andreas Rößler

The Euler scheme is one of the standard schemes to obtain numerical approximations of stochastic differential equations (SDEs). Its convergence properties are well-known in the case of globally Lipschitz continuous coefficients. However, in…

数值分析 · 数学 2019-01-29 S. Göttlich , K. Lux , A. Neuenkirch

We propose a tamed-adaptive Milstein scheme for stochastic differential equations in which the first-order derivatives of the coefficients are locally H\"older continuous of order $\alpha$. We show that the scheme converges in the…

概率论 · 数学 2025-07-10 Thi-Huong Vu , Hoang-Long Ngo , Duc-Trong Luong , Tran Ngoc Khue

We study the strong approximation of stochastic differential equations with discontinuous drift coefficients and (possibly) degenerate diffusion coefficients. To account for the discontinuity of the drift coefficient we construct an…

数值分析 · 数学 2019-04-25 Andreas Neuenkirch , Michaela Szölgyenyi , Lukasz Szpruch

In this paper we study strong approximation of the solution of a scalar stochastic differential equation (SDE) at the final time in the case when the drift coefficient may have discontinuities in space. Recently it has been shown in…

概率论 · 数学 2019-04-22 Thomas Müller-Gronbach , Larisa Yaroslavtseva

This paper is concerned with the numerical approximation of stochastic mechanical systems with nonlinear holonomic constraints. Such systems are described by second order stochastic differential-algebraic equations involving an implicitly…

概率论 · 数学 2017-09-26 Felix Lindner , Holger Stroot
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