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We discuss the application of multistep collocation methods to Volterra integral equations which contain a weakly singular kernel $(t-\tau)^{\alpha-1}$ with $0 <\alpha <1.$ Convergence orders of the methods are determined and their…

Numerical Analysis · Mathematics 2014-12-17 D. Nazari Susahab , S. Shahmorad

We consider equidistant Riemann approximations of stochastic integrals $\int_0^T f(B^H_s)dB^H_s$ with respect to the fractional Brownian motion with $H>\frac12$, where $f$ is an arbitrary function of locally bounded variation, hence…

Probability · Mathematics 2023-05-09 Valentin Garino , Lauri Viitasaari

The explicit Euler scheme and similar explicit approximation schemes (such as the Milstein scheme) are known to diverge strongly and numerically weakly in the case of one-dimensional stochastic ordinary differential equations with…

Numerical Analysis · Mathematics 2019-03-15 Matteo Beccari , Martin Hutzenthaler , Arnulf Jentzen , Ryan Kurniawan , Felix Lindner , Diyora Salimova

This paper extends the derivation of the Lagrangian averaged Euler (LAE-$\alpha$) equations to the case of barotropic compressible flows. The aim of Lagrangian averaging is to regularize the compressible Euler equations by adding dispersion…

Fluid Dynamics · Physics 2007-05-23 H. S. Bhat , R. C. Fetecau , J. E. Marsden , K. Mohseni , M. West

Approximations of the Dirac delta distribution are commonly used to create sequences of smooth functions approximating nonsmooth (generalized) functions, via convolution. In this work, we show a priori rates of convergence of this…

Numerical Analysis · Mathematics 2021-11-18 Luca Heltai , Wenyu Lei

This paper is to explore a model of the ABS Algorithms dealing with the solution of a class of systems of linear stochastic equations $A\xi=\eta$ when $\eta$ is a $m$-dimensional normal distribution. It is shown that the stepsize $\alpha_i$…

Instrumentation and Methods for Astrophysics · Physics 2009-01-27 Hai-Shan Han , Antonino Del Popolo , Zun-Quan Xia

Super- and sub- diffusions are two typical types of anomalous diffusions in the natural world. In this work, we discuss the numerical scheme for the model describing the competition between super- and sub- diffusions driven by fractional…

Numerical Analysis · Mathematics 2022-09-07 Jing Sun , Daxin Nie , Weihua Deng

The stochastic heat equation on the sphere driven by additive L\'evy random field is approximated by a spectral method in space and forward and backward Euler-Maruyama schemes in time, in analogy to the Wiener case. New regularity results…

Probability · Mathematics 2025-07-08 Annika Lang , Andrea Papini , Verena Schwarz

With the use of tensor product of Hilbert space, and a diagonalization procedure from operator theory, we derive an approximation formula for a general class of stochastic integrals. Further we establish a generalized Fourier expansion for…

Mathematical Physics · Physics 2015-05-13 Palle E. T. Jorgensen , Myung-Sin Song

We prove a weak error estimate for the approximation in space and time of a semilinear stochastic Volterra integro-differential equation driven by additive space-time Gaussian noise. We treat this equation in an abstract framework, in which…

Numerical Analysis · Mathematics 2016-03-15 Adam Andersson , Mihály Kovács , Stig Larsson

This paper deals with the weak error estimates of the exponential Euler method for semi-linear stochastic partial differential equations (SPDEs). A weak error representation formula is first derived for the exponential integrator scheme in…

Numerical Analysis · Mathematics 2015-06-23 Xiaojie Wang

Stochastic averaging for a class of stochastic differential equations (SDEs) with fractional Brownian motion, of the Hurst parameter H in the interval (1/2, 1), is investigated. An averaged SDE for the original SDE is proposed, and their…

Dynamical Systems · Mathematics 2013-01-22 Yong Xu , Rong Guo , Di Liu , Huiqing Zhang , Jinqiao Duan

We propose a general algorithm for approximating nonstandard Bayesian posterior distributions. The algorithm minimizes the Kullback-Leibler divergence of an approximating distribution to the intractable posterior distribution. Our method…

Computation · Statistics 2014-07-29 Tim Salimans , David A. Knowles

This paper adopts a highly effective numerical approach for approximating non-linear stochastic Volterra integral equations (NLSVIEs) based on the operational matrices of the Walsh function and the collocation method. The method transforms…

Numerical Analysis · Mathematics 2023-11-30 Prit Pritam Paikaray , Nigam Chandra Parida , Sanghamitra Beuria , Omid Nikan

We consider an incremental approximation method for solving variational problems in infinite-dimensional Hilbert spaces, where in each step a randomly and independently selected subproblem from an infinite collection of subproblems is…

Numerical Analysis · Mathematics 2018-03-06 Michael Griebel , Peter Oswald

In this article we establish central limit theorems for multilevel Polyak-Ruppert averaged stochastic approximation schemes. We work under very mild technical assumptions and consider the slow regime in wich typical errors decay like…

Probability · Mathematics 2019-12-18 Steffen Dereich

In this paper, we refine the Berry-Esseen bounds for the multivariate normal approximation of Polyak-Ruppert averaged iterates arising from the linear stochastic approximation (LSA) algorithm with decreasing step size. We consider the…

Machine Learning · Statistics 2025-10-15 Bogdan Butyrin , Eric Moulines , Alexey Naumov , Sergey Samsonov , Qi-Man Shao , Zhuo-Song Zhang

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…

Numerical Analysis · Mathematics 2019-01-29 S. Göttlich , K. Lux , A. Neuenkirch

The systems of nonlinear Volterra integral equations of the first kind with jump discontinuous kernels are studied. The iterative numerical method for such nonlinear systems is proposed. Proposed method employs the modified…

Numerical Analysis · Mathematics 2019-10-22 A. N. Tynda , D. N. Sidorov , N. A. Sidorov

In this paper the numerical approximation of stochastic differential equations satisfying a global monotonicity condition is studied. The strong rate of convergence with respect to the mean square norm is determined to be $\frac{1}{2}$ for…

Numerical Analysis · Mathematics 2017-09-01 Adam Andersson , Raphael Kruse