English
Related papers

Related papers: On Quasi-Monte Carlo Methods in Weighted ANOVA Spa…

200 papers

Classical algorithms in numerical analysis for numerical integration (quadrature/cubature) follow the principle of approximate and integrate: the integrand is approximated by a simple function (e.g. a polynomial), which is then integrated…

Numerical Analysis · Mathematics 2018-06-15 Yuji Nakatsukasa

This paper considers two notions of effective dimension for quadrature in weighted pre-Sobolev spaces with dominating mixed partial derivatives. We begin by finding a ball in those spaces just barely large enough to contain a function with…

Numerical Analysis · Mathematics 2018-12-04 Art B. Owen

Antithetic sampling, which goes back to the classical work by Hammersley and Morton (1956), is one of the well-known variance reduction techniques for Monte Carlo integration. In this paper we investigate its application to digital nets…

Numerical Analysis · Mathematics 2019-12-09 Takashi Goda

The classical approaches to numerically integrating a function $f$ are Monte Carlo (MC) and quasi-Monte Carlo (QMC) methods. MC methods use random samples to evaluate $f$ and have error $O(\sigma(f)/\sqrt{n})$, where $\sigma(f)$ is the…

Data Structures and Algorithms · Computer Science 2024-08-14 Nikhil Bansal , Haotian Jiang

We design a quasi-interpolation operator from the Sobolev space $H^1_0(\Omega)$ to its finite-dimensional finite element subspace formed by piecewise polynomials on a simplicial mesh with a computable approximation constant. The operator 1)…

Numerical Analysis · Mathematics 2025-07-17 T. Chaumont-Frelet , M. Vohralik

Monte Carlo integration is a commonly used technique to compute intractable integrals and is typically thought to perform poorly for very high-dimensional integrals. To show that this is not always the case, we examine Monte Carlo…

Methodology · Statistics 2023-05-26 Yanbo Tang

Importance sampling Monte-Carlo methods are widely used for the approximation of expectations with respect to partially known probability measures. In this paper we study a deterministic version of such an estimator based on quasi-Monte…

Computation · Statistics 2024-12-20 Josef Dick , Daniel Rudolf , Houying Zhu

In this paper, we develop and test a fast numerical algorithm, called MDI-LR, for efficient implementation of quasi-Monte Carlo lattice rules for computing $d$-dimensional integrals of a given function. It is based on the idea of converting…

Numerical Analysis · Mathematics 2024-04-16 Huicong Zhong , Xiaobing Feng

We study optimal quadrature formulas for arbitrary weighted integrals and integrands from the Sobolev space $H^1([0,1])$. We obtain general formulas for the worst case error depending on the nodes $x_j$. A particular case is the computation…

Numerical Analysis · Mathematics 2018-07-17 Erich Novak , Shun Zhang

We prove that the covering radius of an $N$-point subset $X_N$ of the unit sphere $S^d \subset R^{d+1}$ is bounded above by a power of the worst-case error for equal weight cubature $\frac{1}{N}\sum_{\mathbf{x} \in X_N}f(\mathbf{x}) \approx…

Numerical Analysis · Mathematics 2017-07-27 Johann S. Brauchart , Josef Dick , Edward B. Saff , Ian H. Sloan , Yu Guang Wang , Robert S. Womersley

In a recent paper Keister proposed two quadrature rules as alternatives to Monte Carlo for certain multidimensional integrals and reported his test results. In earlier work we had shown that the quasi-Monte Carlo method with generalized…

Computational Physics · Physics 2015-06-26 A. Papageorgiou , J. F. Traub

We show how simple kinks and jumps of otherwise smooth integrands over $\mathbb{R}^d$ can be dealt with by a preliminary integration with respect to a single well chosen variable. It is assumed that this preintegration, or conditional…

Numerical Analysis · Mathematics 2017-12-05 Andreas Griewank , Frances Y. Kuo , Hernan Leövey , Ian H. Sloan

In this article we design a novel quasi-regression Monte Carlo algorithm in order to approximate the solution of discrete time backward stochastic differential equations (BSDEs), and we analyze the convergence of the proposed method. The…

Numerical Analysis · Mathematics 2024-08-01 E. Gobet , J. G. López-Salas , C. Vázquez

This paper studies randomized quasi-Monte Carlo (QMC) sampling for discontinuous integrands having singularities along the boundary of the unit cube $[0,1]^d$. Both discontinuities and singularities are extremely common in the pricing and…

Numerical Analysis · Mathematics 2017-06-26 Zhijian He

Monte Carlo methods are widely used in particle physics to integrate and sample probability distributions (differential cross sections or decay rates) on multi-dimensional phase spaces. We present a Neural Network (NN) algorithm optimized…

High Energy Physics - Phenomenology · Physics 2020-10-21 Matthew D. Klimek , Maxim Perelstein

We show how information on the uniformity properties of a point set employed in numerical multidimensional integration can be used to improve the error estimate over the usual Monte Carlo one. We introduce a new measure of (non-)uniformity…

High Energy Physics - Phenomenology · Physics 2009-10-28 Jiri Hoogland , Ronald Kleiss

We develop algorithms for multivariate integration and approximation in the weighted half-period cosine space of smooth non-periodic functions. We use specially constructed tent-transformed rank-1 lattice points as cubature nodes for…

Numerical Analysis · Mathematics 2016-06-03 Ronald Cools , Frances Y. Kuo , Dirk Nuyens , Gowri Suryanarayana

QMC rules are equal weight quadrature rules for approximating integrals over $[0,1]^s$. One line of research studies the integration error of functions in the unit ball of so-called Korobov spaces, which are Hilbert spaces of periodic…

Numerical Analysis · Mathematics 2014-11-12 Josef Dick , Peter Kritzer , Gunther Leobacher , Friedrich Pillichshammer

This is basically a review of the field of Quasi-Monte Carlo intended for computational physicists and other potential users of quasi-random numbers. As such, much of the material is not new, but is presented here in a style hopefully more…

High Energy Physics - Phenomenology · Physics 2010-11-11 Fred James , Jiri Hoogland , Ronald Kleiss

Consider the numerical integration $${\rm Int}_{\mathbb S^d,w}(f)=\int_{\mathbb S^d}f({\bf x})w({\bf x}){\rm d}\sigma({\bf x}) $$ for weighted Sobolev classes $BW_{p,w}^r(\mathbb S^d)$ with a Dunkl weight $w$ and weighted Besov classes…

Numerical Analysis · Mathematics 2024-12-24 Jiansong Li , Heping Wang
‹ Prev 1 3 4 5 6 7 10 Next ›