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In this paper we construct polynomial lattice rules which have, in some sense, small gain coefficients using a component-by-component approach. The gain coefficients, as introduced by Owen, indicate to what degree the method improves upon…

Numerical Analysis · Mathematics 2010-04-07 Jan Baldeaux , Josef Dick

The weighted star discrepancy is a quantitative measure for the performance of point sets in quasi-Monte Carlo algorithms for numerical integration. We consider polynomial lattice point sets, whose generating vectors can be obtained by a…

Number Theory · Mathematics 2020-05-28 Ralph Kritzinger , Helene Laimer , Mario Neumüller

We study numerical integration on the unit sphere $\mathbb{S}^2 \subset \mathbb{R}^3$ using equal weight quadrature rules, where the weights are such that constant functions are integrated exactly. The quadrature points are constructed by…

Numerical Analysis · Mathematics 2014-02-17 Johann S. Brauchart , Josef Dick

Higher order scrambled digital nets are randomized quasi-Monte Carlo rules which have recently been introduced in [J. Dick, Ann. Statist., 39 (2011), 1372--1398] and shown to achieve the optimal rate of convergence of the root mean square…

Numerical Analysis · Mathematics 2019-12-09 Takashi Goda , Josef Dick

We study multivariate numerical integration of smooth functions in weighted Sobolev spaces with dominating mixed smoothness $\alpha\geq 2$ defined over the $s$-dimensional unit cube. We propose a new quasi-Monte Carlo (QMC)-based quadrature…

Numerical Analysis · Mathematics 2019-12-09 Josef Dick , Takashi Goda , Takehito Yoshiki

We study multivariate integration over the $s$-dimensional unit cube in a weighted space of infinitely differentiable functions. It is known from a recent result by Suzuki that there exists a good quasi-Monte Carlo (QMC) rule which achieves…

Numerical Analysis · Mathematics 2019-12-09 Josef Dick , Takashi Goda , Kosuke Suzuki , Takehito Yoshiki

We study the efficient construction of good polynomial lattice rules, which are special instances of quasi-Monte Carlo (QMC) methods. The integration rules obtained are of particular interest for the approximation of multivariate integrals…

Numerical Analysis · Mathematics 2021-02-01 Adrian Ebert , Peter Kritzer , Onyekachi Osisiogu , Tetiana Stepaniuk

In this note, we study a concatenation of quasi-Monte Carlo and plain Monte Carlo rules for high-dimensional numerical integration in weighted function spaces. In particular, we consider approximating the integral of periodic functions…

Numerical Analysis · Mathematics 2022-06-27 Takashi Goda

The weighted star discrepancy of point sets appears in the weighted Koksma-Hlawka inequality and thus is a measure for the quality of point sets with respect to their performance in quasi-Monte Carlo algorithms. A special choice of point…

Number Theory · Mathematics 2015-11-30 Ralph Kritzinger , Helene Laimer

Monte Carlo (MC) and Quasi-Monte Carlo (QMC) methods are classical approaches for the numerical integration of functions $f$ over $[0,1]^d$. While QMC methods can achieve faster convergence rates than MC in moderate dimensions, their…

Numerical Analysis · Mathematics 2025-08-27 Jiaheng Chen , Haotian Jiang , Nathan Kirk

In this paper, we study the problem of multivariate $L_2$-approximation of functions belonging to a weighted Korobov space. We propose and analyze a median lattice-based algorithm, inspired by median integration rules, which have attracted…

Numerical Analysis · Mathematics 2025-11-04 Zexin Pan , Peter Kritzer , Takashi Goda

A comprehensive overview of lattice rules and polynomial lattice rules is given for function spaces based on $\ell_p$ semi-norms. Good lattice rules and polynomial lattice rules are defined as those obtaining worst-case errors bounded by…

Numerical Analysis · Mathematics 2020-07-20 Dirk Nuyens

Lattice rules and polynomial lattice rules are quadrature rules for approximating integrals over the $s$-dimensional unit cube. Since no explicit constructions of such quadrature methods are known for dimensions $s > 2$, one usually has to…

Numerical Analysis · Mathematics 2014-04-23 Josef Dick , Peter Kritzer , Gunther Leobacher , Friedrich Pillichshammer

We study quasi-Monte Carlo (QMC) methods for numerical integration of multivariate functions defined over the high-dimensional unit cube. Lattice rules and polynomial lattice rules, which are special classes of QMC methods, have been…

Numerical Analysis · Mathematics 2020-06-23 Josef Dick , Takashi Goda

We consider the efficient construction of polynomial lattice rules, which are special cases of so-called quasi-Monte Carlo (QMC) rules. These are of particular interest for the approximate computation of multivariate integrals where the…

Numerical Analysis · Mathematics 2020-08-21 Adrian Ebert , Peter Kritzer , Onyekachi Osisiogu , Tetiana Stepaniuk

In this paper, we study an efficient algorithm for constructing node sets of high-quality quasi-Monte Carlo integration rules for weighted Korobov, Walsh, and Sobolev spaces. The algorithm presented is a reduced fast successive coordinate…

Numerical Analysis · Mathematics 2020-04-08 Adrian Ebert , Peter Kritzer

Quasi-Monte Carlo (QMC) methods are equal weight quadrature rules to approximate integrals over the unit cube with respect to the uniform measure. In this paper we discuss QMC integration with respect to general product measures defined on…

Numerical Analysis · Mathematics 2020-09-16 Josef Dick , Friedrich Pillichshammer

In this paper we give explicit constructions of point sets in the $s$ dimensional unit cube yielding quasi-Monte Carlo algorithms which achieve the optimal rate of convergence of the worst-case error for numerically integrating high…

Numerical Analysis · Mathematics 2013-04-02 Josef Dick

We show that the $\mathcal{L}_2$ discrepancy of the explicitly constructed infinite sequences of points $(\boldsymbol{x}_0,\boldsymbol{x}_1, \boldsymbol{x}_2,...)$ in $[0,1)^s$ over $\mathbb{F}_2$ introduced in [J. Dick, Walsh spaces…

Number Theory · Mathematics 2013-06-04 Josef Dick , Friedrich Pillichshammer

We consider the problem of evaluating $I(\varphi):=\int_{[0,1)^s}\varphi(x) dx$ for a function $\varphi \in L^2[0,1)^{s}$. In situations where $I(\varphi)$ can be approximated by an estimate of the form $N^{-1}\sum_{n=0}^{N-1}\varphi(x^n)$,…

Computation · Statistics 2015-06-09 Mathieu Gerber
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