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In this paper we study lattice rules which are cubature formulae to approximate integrands over the unit cube $[0,1]^s$ from a weighted reproducing kernel Hilbert space. We assume that the weights are independent random variables with a…

Numerical Analysis · Mathematics 2011-09-26 Josef Dick

Several more and more efficient component--by--component (CBC) constructions for suitable rank-1 lattices were developed during the last decades. On the one hand, there exist constructions that are based on minimizing some error functional.…

Numerical Analysis · Mathematics 2020-12-29 Lutz Kämmerer

This paper studies the multivariate approximation of functions in weighted Korobov spaces using multiple rank-1 lattice rules. It has been shown by K\"{a}mmerer and Volkmer (2019) that algorithms based on multiple rank-1 lattices achieve…

Numerical Analysis · Mathematics 2026-04-03 Mou Cai , Takashi Goda

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

High dimensional integrals are abundant in many fields of research including quantum physics. The aim of this paper is to develop efficient recursive strategies to tackle a class of high dimensional integrals having a special product…

Numerical Analysis · Mathematics 2021-07-28 Tobias Hartung , Karl Jansen , Frances Y. Kuo , Hernan Leövey , Dirk Nuyens , Ian H. Sloan

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 study multivariate integration of functions that are invariant under permutations (of subsets) of their arguments. We find an upper bound for the $n$th minimal worst case error and show that under certain conditions, it can be bounded…

Numerical Analysis · Mathematics 2015-03-10 Dirk Nuyens , Gowri Suryanarayana , Markus Weimar

Lattice rules are among the most prominently studied quasi-Monte Carlo methods to approximate multivariate integrals. A rank-1 lattice rule to approximate an $s$-dimensional integral is fully specified by its generating vector $\mathbf{z}…

Numerical Analysis · Mathematics 2020-01-10 Adrian Ebert , Peter Kritzer , Dirk Nuyens , Onyekachi Osisiogu

We study multivariate integration of functions that are invariant under the permutation (of a subset) of their arguments. Recently, in Nuyens, Suryanarayana, and Weimar (Adv. Comput. Math. (2016), 42(1):55--84), the authors derived an upper…

Numerical Analysis · Mathematics 2016-11-29 Dirk Nuyens , Gowri Suryanarayana , Markus Weimar

We study a randomized quadrature algorithm to approximate the integral of periodic functions defined over the high-dimensional unit cube. Recent work by Kritzer, Kuo, Nuyens and Ullrich (2019) shows that rank-1 lattice rules with a randomly…

Numerical Analysis · Mathematics 2023-04-28 Josef Dick , Takashi Goda , Kosuke Suzuki

Quasi-Monte Carlo (QMC) is an essential tool for integral approximation, Bayesian inference, and sampling for simulation in science, etc. In the QMC area, the rank-1 lattice is important due to its simple operation, and nice properties for…

Computation · Statistics 2020-11-13 Yueming Lyu , Yuan Yuan , Ivor W. Tsang

The (fast) component-by-component (CBC) algorithm is an efficient tool for the construction of generating vectors for quasi-Monte Carlo rank-1 lattice rules in weighted reproducing kernel Hilbert spaces. We consider product weights, which…

Numerical Analysis · Mathematics 2017-11-06 Adrian Ebert , Hernan Leövey , Dirk Nuyens

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

Kernel-based quadrature rules are becoming important in machine learning and statistics, as they achieve super-$\sqrt{n}$ convergence rates in numerical integration, and thus provide alternatives to Monte Carlo integration in challenging…

Machine Learning · Statistics 2016-10-31 Motonobu Kanagawa , Bharath K. Sriperumbudur , Kenji Fukumizu

Lattice rules are among the most prominently studied quasi-Monte Carlo methods to approximate multivariate integrals. A rank-$1$ lattice rule to approximate an $s$-dimensional integral is fully specified by its \emph{generating vector}…

Numerical Analysis · Mathematics 2023-01-02 Peter Kritzer

We consider the approximate recovery of multivariate periodic functions from a discrete set of function values taken on a rank-$s$ integration lattice. The main result is the fact that any (non-)linear reconstruction algorithm taking…

Numerical Analysis · Mathematics 2016-08-02 Glenn Byrenheid , Lutz Kämmerer , Tino Ullrich , Toni Volkmer

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

The aim of this paper is to show that one can achieve convergence rates of $N^{-\alpha+ \delta}$ for $\alpha > 1/2$ (and for $\delta > 0$ arbitrarily small) for nonperiodic $\alpha$-smooth cosine series using lattice rules without random…

Numerical Analysis · Mathematics 2012-11-19 Josef Dick , Dirk Nuyens , Friedrich Pillichshammer

This paper investigates the construction of space-filling designs for computer experiments. The space-filling property is characterized by the covering and separation radii of a design, which are integrated through the unified criterion of…

Methodology · Statistics 2026-02-18 Naoki Sakai , Takashi Goda

We seek shifted lattice rules that are good for high dimensional integration over the unit cube in the setting of an unanchored weighted Sobolev space of functions with square-integrable mixed first derivatives. Many existing studies rely…

Numerical Analysis · Mathematics 2019-03-14 Yoshihito Kazashi , Frances Y. Kuo , Ian H. Sloan
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