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Related papers: Numerical schemes for radial Dunkl processes

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We establish an equivalence between two classes of methods for solving fractional diffusion problems, namely, Reduced Basis Methods (RBM) and Rational Krylov Methods (RKM). In particular, we demonstrate that several recently proposed RBMs…

Numerical Analysis · Mathematics 2021-03-01 Tobias Danczul , Clemens Hofreither

We investigate some recursive procedures based on an exact or ``approximate'' Euler scheme with decreasing step in vue to computation of invariant measures of solutions to S.D.E. driven by a L\'evy process. Our results are valid for a large…

Probability · Mathematics 2008-04-02 Fabien Panloup

We propose a new scheme for the long time approximation of a diffusion when the drift vector field is not globally Lipschitz. Under this assumption, regular explicit Euler scheme --with constant or decreasing step-- may explode and implicit…

Probability · Mathematics 2018-02-20 Vincent Lemaire

In this article, we consider the radial Dunkl geometric case $k=1$ corresponding to flat Riemannian symmetric spaces in the complex case and we prove exact estimates for the positive valued Dunkl kernel and for the radial heat kernel. Dans…

Representation Theory · Mathematics 2020-12-23 P. Graczyk , P. Sawyer

Since it is difficult to implement implicit schemes on the infinite-dimensional space, we aim to develop the explicit numerical method for approximating super-linear stochastic functional differential equations (SFDEs). Precisely, borrowing…

Numerical Analysis · Mathematics 2022-08-23 Xiaoyue Li , Xuerong Mao , Guoting Song

We consider a general class of high order weak approximation schemes for stochastic differential equations driven by L\'evy processes with infinite activity. These schemes combine a compound Poisson approximation for the jump part of the…

Probability · Mathematics 2012-04-24 Arturo Kohatsu-Higa , Salvador Ortiz-Latorre , Peter Tankov

Piecewise $\alpha$-stable Ornstein-Uhlenbeck (OU) processes arising in queue networks usually do not have an explicit dissipation, which makes the related numerical methods such as Euler-Maruyama (EM) scheme more difficult to analyze. We…

Probability · Mathematics 2024-11-11 Xinghu Jin , Guodong Pang , Yu Wang , Lihu Xu

In this article we study the Dyson Bessel process, which describes the evolution of singular values of rectangular matrix Brownian motions, and prove a large deviation principle for its empirical particle density. We then use it to obtain…

Probability · Mathematics 2021-06-15 Alice Guionnet , Jiaoyang Huang

We investigate smooth approximations of functions, with prescribed gradient behavior on a distinguished stratified subset of the domain. As an application, we outline how our results yield important consequences for a recently introduced…

Classical Analysis and ODEs · Mathematics 2015-07-21 D. Drusvyatskiy , M. Larsson

The well-known Koml\'os-Major-Tusn\'ady inequalities [Z. Wahrsch. Verw. Gebiete 32 (1975) 111-131; Z. Wahrsch. Verw. Gebiete 34 (1976) 33-58] provide sharp inequalities to partial sums of iid standard exponential random variables by a…

Statistics Theory · Mathematics 2017-12-11 Abdelhakim Necir

In Mergelyan type approximation we uniformly approximate functions on compact sets K by polynomials or rational functions or holomorphic functions on varying open sets containing K. In the present paper we consider analogous approximation,…

Complex Variables · Mathematics 2020-06-04 Sotiris Armeniakos , Giorgos Kotsovolis , Vassili Nestoridis

We consider a branching Brownian motion in $\mathbb{R}^d$ with $d \geq 1$ in which the position $X_t^{(u)}\in \mathbb{R}^d$ of a particle $u$ at time $t$ can be encoded by its direction $\theta^{(u)}_t \in \mathbb{S}^{d-1}$ and its distance…

Probability · Mathematics 2023-12-01 Julien Berestycki , Yujin H. Kim , Eyal Lubetzky , Bastien Mallein , Ofer Zeitouni

We consider the problem of approximating partition functions for Ising models. We make use of recent tools in combinatorial optimization: the Sherali-Adams and Lasserre convex programming hierarchies, in combination with variational methods…

Machine Learning · Computer Science 2016-07-13 Andrej Risteski

We consider a second order differential operator $A(\msx) = -\:\sum_{i,j=1}^d \partial_i a_{ij}(\msx) \partial_j \:+\: \sum_{j=1}^d \partial_j \big(b_j(\msx) \cdot \big)\:+\: c(\msx)$ on ${\bbR}^d$, on a bounded domain $D$ with Dirichlet…

Analysis of PDEs · Mathematics 2007-12-24 Nedzad Limić , Mladen Rogina

We consider stochastic differential equations in a Hilbert space, perturbed by the gradient of a convex potential. We investigate the problem of convergence of a sequence of such processes. We propose applications of this method to…

Probability · Mathematics 2007-05-23 Lorenzo Zambotti

In this paper, we provide the strong rate of convergence for the Euler--Maruyama scheme for multi-dimensional stochastic differential equations with uniformly locally (unbounded) H\"older continuous drift and multiplicative noise. Our…

Probability · Mathematics 2026-01-09 Tsukasa Moritoki , Dai Taguchi

In this paper, we investigate the weak convergence rate of Euler-Maruyama's approximation for stochastic differential equations with irregular drifts. Explicit weak convergence rates are presented if drifts satisfy an integrability…

Probability · Mathematics 2020-05-12 Yongqiang Suo , Chenggui Yuan , Shao-Qin Zhang

A practical and accessible introduction to most probable phase portraits is given. The reader is assumed to be familiar with stochastic differential equations and Euler-Maruyama method in numerical simulation. The article first introduce…

Probability · Mathematics 2017-03-21 Bing Yang , Zhu Zeng , Ling Wang

A new class of explicit Euler schemes, which approximate stochastic differential equations (SDEs) with superlinearly growing drift and diffusion coefficients, is proposed in this article. It is shown, under very mild conditions, that these…

Probability · Mathematics 2016-09-05 Sotirios Sabanis

This paper establishes a discretization scheme for a large class of stochastic differential equations driven by a time-changed Brownian motion with drift, where the time change is given by a general inverse subordinator. The scheme involves…

Probability · Mathematics 2015-11-13 Ernest Jum , Kei Kobayashi