activity
20172024
most citedMultivariate stable approximation in Wasserstein distance by Stein's method

8 citations · 17 across the 11 of their papers we have counts for

collaborators

12 papers

math.PR2024

-convergence rate of EM schemes for invariant measures of supercritical stable SDEs

Peng Chen, Lihu Xu, Xiaolong Zhang +1

By establishing the regularity estimates for nonlocal Stein/Poisson equations under -order Hölder and dissipative conditions on the coefficients, we derive the -conve…

math.PR2024

Quantitative diffusion approximation for the Neutral -Alleles Wright-Fisher Model with Mutations

Peng Chen, Jie Xiong, Lihu Xu +1

We apply a Lindeberg principle under the Markov process setting to approximate the Wright-Fisher model with neutral -alleles using a diffusion process, deriving an error rate ba…

math.PR2023★ 1 cited

Approximation of the invariant measure for stable SDE by the Euler-Maruyama scheme with decreasing step-sizes

Peng Chen, Xinghu Jin, Yimin Xiao +1

Let be the solution of the stochastic differential equation where is a Lipsc…

math.PR2022

Approximation of the invariant measure of stable SDEs by an Euler--Maruyama scheme

Peng Chen, Changsong Deng, Rene Schilling +1

We propose two Euler-Maruyama (EM) type numerical schemes in order to approximate the invariant measure of a stochastic differential equation (SDE) driven by an -stable Lévy pro…

math.PR2021

Approximation to stochastic variance reduced gradient Langevin dynamics by stochastic delay differential equations

Peng Chen, Jianya Lu, Lihu Xu

We study in this paper a weak approximation to stochastic variance reduced gradient Langevin dynamics by stochastic delay differential equations in Wasserstein-1 distance, and obta…

math.PR2020

A probability approximation framework: Markov process approach

Peng Chen, Qi-Man Shao, Lihu Xu

We view the classical Lindeberg principle in a Markov process setting to establish a probability approximation framework by the associated Itô's formula and Markov operator. As app…

math.ST2020★ 1 cited

A generalized Catoni's -estimator under finite {-th moment assumption} with

Peng Chen, Xinghu Jin, Xiang Li +1

We generalize the { -estimator} put forward by Catoni in his seminal paper [C12] to the case in which samples can have finite -th moment with rather than f…

math.PR2019★ 8 cited

Multivariate stable approximation in Wasserstein distance by Stein's method

Peng Chen, Ivan Nourdin, Lihu Xu +1

By a delicate analysis for the Stein's equation associated to the -stable law approximation with , we prove a quantitative stable central limit theorem in Wasserstei…

math.PR2019★ 4 cited

Non-integrable stable approximation by Stein's method

Peng Chen, Ivan Nourdin, Lihu Xu +2

We develop Stein's method for -stable approximation with , continuing the recent line of research by Xu \cite{lihu} and Chen, Nourdin and Xu \cite{C-N-X} in the case…

math.PR2018

Stein's method for asymmetric -stable distributions, with application to the stable CLT

Peng Chen, Ivan Nourdin, Lihu Xu

This paper is concerned with the Stein's method associated with a (possibly) asymmetric -stable distribution , in dimension one. More precisely, its goal is twofold. In the f…

math.PR2018★ 1 cited

Approximation to the stable law by Lindeberg principle

Peng Chen, Lihu Xu

By the Lindeberg principle, we develop in this paper an approximation to one dimensional (possibly) asymmetric -stable distributions with in the smooth Wasserstein…

math.PR2017★ 2 cited

Heat kernel estimates for Dirichlet fractional Laplacian with gradient perturbation

Peng Chen, Renming Song, Longjie Xie +1

We give a direct proof of the sharp two-sided estimates, recently established in [4,9], for the Dirichlet heat kernel of the fractional Laplacian with gradient perturbation in $C^{…