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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 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

In this paper, we study an efficient algorithm for constructing point sets underlying quasi-Monte Carlo integration rules for weighted Korobov classes. The algorithm presented is a reduced fast component-by-component digit-by-digit…

Numerical Analysis · Mathematics 2022-11-23 Peter Kritzer , Onyekachi Osisiogu

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

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 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

In a recent paper by the same authors, we provided a theoretical foundation for the component-by-component (CBC) construction of lattice algorithms for multivariate $L_2$ approximation in the worst case setting, for functions in a periodic…

Numerical Analysis · Mathematics 2019-10-16 Ronald Cools , Frances Y. Kuo , Dirk Nuyens , Ian H. Sloan

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

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

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 show that a very simple randomised algorithm for numerical integration can produce a near optimal rate of convergence for integrals of functions in the $d$-dimensional weighted Korobov space. This algorithm uses a lattice rule with a…

Numerical Analysis · Mathematics 2023-04-21 Frances Y. Kuo , Dirk Nuyens , Laurence Wilkes

The component-by-component construction is the standard method of finding good lattice rules or polynomial lattice rules for numerical integration. Several authors have reported that in numerical experiments the generating vector sometimes…

Numerical Analysis · Mathematics 2015-06-29 Josef Dick , Peter Kritzer

In the analysis of using quasi-Monte Carlo (QMC) methods to approximate expectations of a linear functional of the solution of an elliptic PDE with random diffusion coefficient the sensitivity w.r.t. the parameters is often stated in terms…

Numerical Analysis · Mathematics 2019-03-01 Adrian Ebert , Peter Kritzer , Dirk Nuyens

We analyze a new random algorithm for numerical integration of $d$-variate functions over $[0,1]^d$ from a weighted Sobolev space with dominating mixed smoothness $\alpha\ge 0$ and product weights $1\ge\gamma_1\ge\gamma_2\ge\cdots>0$, where…

Numerical Analysis · Mathematics 2019-08-15 Peter Kritzer , Frances Y. Kuo , Dirk Nuyens , Mario Ullrich

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

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

We study the multivariate integration problem for periodic functions from the weighted Korobov space in the randomized setting. We introduce a new randomized rank-1 lattice rule with a randomly chosen number of points, which avoids the need…

Numerical Analysis · Mathematics 2024-11-19 Takashi Goda

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 paper we investigate multivariate integration in weighted unanchored Sobolev spaces of smoothness of arbitrarily high order. As quadrature points we employ higher order polynomial lattice point sets over $\mathbb{F}_{2}$ which are…

Numerical Analysis · Mathematics 2019-12-09 Takashi Goda

We approximate $d$-variate periodic functions in weighted Korobov spaces with general weight parameters using $n$ function values at lattice points. We do not limit $n$ to be a prime number, as in currently available literature, but allow…

Numerical Analysis · Mathematics 2022-09-05 Frances Y. Kuo , Weiwen Mo , Dirk Nuyens
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