English
Related papers

Related papers: Probabilistic discrepancy bound for Monte Carlo po…

200 papers

We study some notions of negative dependence of a sampling scheme that can be used to derive variance bounds for the corresponding estimator or discrepancy bounds for the underlying random point set that are at least as good as the…

Numerical Analysis · Mathematics 2021-02-10 Michael Gnewuch , Marcin Wnuk , Nils Hebbinghaus

In this paper we study uniform distribution properties of digital sequences over a finite field of prime order. In 1998 it was shown by Larcher that for almost all $s$-dimensional digital sequences the star discrepancy $D_N^\ast$ satisfies…

Number Theory · Mathematics 2013-02-19 Gerhard Larcher , Friedrich Pillichshammer

We present a new algorithm for estimating the star discrepancy of arbitrary point sets. Similar to the algorithm for discrepancy approximation of Winker and Fang [SIAM J. Numer. Anal. 34 (1997), 2028--2042] it is based on the optimization…

Data Structures and Algorithms · Computer Science 2021-09-21 Michael Gnewuch , Magnus Wahlström , Carola Winzen

In the present paper we prove several results concerning the existence of low-discrepancy point sets with respect to an arbitrary non-uniform measure $\mu$ on the $d$-dimensional unit cube. We improve a theorem of Beck, by showing that for…

Number Theory · Mathematics 2013-08-26 Christoph Aistleitner , Josef Dick

The $L_{\infty}$ star discrepancy is a very well-studied measure used to quantify the uniformity of a point set distribution. Constructing optimal point sets for this measure is seen as a very hard problem in the discrepancy community.…

Computational Geometry · Computer Science 2024-02-28 François Clément , Carola Doerr , Kathrin Klamroth , Luís Paquete

For a probability measure $\mu$ on $[0,1]$ without discrete component, the best possible order of approximation by a finite point set in terms of the star-discrepancy is $\frac{1}{2N}$ as has been proven relatively recently. However, if…

Number Theory · Mathematics 2022-02-04 Christian Weiß

Geometric discrepancies are standard measures to quantify the irregularity of distributions. They are an important notion in numerical integration. One of the most important discrepancy notions is the so-called \emph{star discrepancy}.…

Neural and Evolutionary Computing · Computer Science 2013-10-08 Carola Doerr , Francois-Michel De Rainville

We consider an acceptance-rejection sampler based on a deterministic driver sequence. The deterministic sequence is chosen such that the discrepancy between the empirical target distribution and the target distribution is small. We use…

Statistics Theory · Mathematics 2014-05-06 Houying Zhu , Josef Dick

We discuss the problem of defining an estimate for the error in quasi-Monte Carlo integration. The key issue is the definition of an ensemble of quasi-random point sets that, on the one hand, includes a sufficiency of equivalent point sets,…

Computational Physics · Physics 2008-02-03 Fred James , Jiri Hoogland , Ronald Kleiss

The choice of a point set, to be used in numerical integration, determines, to a large extent, the error estimate of the integral. Point sets can be characterized by their discrepancy, which is a measure of its non-uniformity. Point sets…

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

Following a result of D.~Bylik and M.T.~Lacey from 2008 it is known that there exists an absolute constant $\eta>0$ such that the (unnormalized) $L^{\infty}$-norm of the three-dimensional discrepancy function, i.e, the (unnormalized) star…

Number Theory · Mathematics 2020-09-15 Florian Puchhammer

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

We provide an algorithm to approximate a finitely supported discrete measure $\mu$ by a measure $\nu_{N}$ corresponding to a set of $N$ points so that the total variation between $\mu$ and $\nu_N$ has an upper bound. As a consequence if…

Number Theory · Mathematics 2022-07-11 Samantha Fairchild , Max Goering , Christian Weiß

We establish sharp non-asymptotic probabilistic bounds for the star discrepancy of double-infinite random matrices -- a canonical model for sequences of random point sets in high dimensions. By integrating the recently proved…

Statistics Theory · Mathematics 2026-01-09 Xiaoda Xu , Jun Xian

We study the extreme and the periodic $L_p$ discrepancy of point sets in the $d$-dimensional unit cube. The extreme discrepancy uses arbitrary sub-intervals of the unit cube as test sets, whereas the periodic discrepancy is based on…

Number Theory · Mathematics 2021-09-14 Ralph Kritzinger , Friedrich Pillichshammer

The determinant lower bound of Lovasz, Spencer, and Vesztergombi [European Journal of Combinatorics, 1986] is a powerful general way to prove lower bounds on the hereditary discrepancy of a set system. In their paper, Lovasz, Spencer, and…

Combinatorics · Mathematics 2024-01-18 Lily Li , Aleksandar Nikolov

We present two main contributions to the expected star discrepancy theory. First, we derive a sharper expected upper bound for jittered sampling, improving the leading constants and logarithmic terms compared to the state-of-the-art [Doerr,…

Statistics Theory · Mathematics 2026-01-09 Xiaoda Xu , Jun Xian

We introduce a class of convex equivolume partitions. Expected star discrepancy results are compared for stratified samples under these partitions, including simple random samples. There are four main parts of our results. First, among…

Statistics Theory · Mathematics 2022-03-08 Jun Xian , Xiaoda Xu , Xinkai Zhou

We prove a generalized Faulhaber inequality to bound the sums of the $j$-th powers of the first $n$ (possibly shifted) natural numbers. With the help of this inequality we are able to improve the known bounds for bracketing numbers of…

Combinatorics · Mathematics 2022-02-11 Michael Gnewuch , Hendrik Pasing , Christian Weiß

Given a real symmetric positive semi-definite matrix E, and an approximation S that is a sum of n independent matrix-valued random variables, we present bounds on the relative error in S due to randomization. The bounds do not depend on the…

Numerical Analysis · Mathematics 2018-01-03 John T. Holodnak , Ilse C. F. Ipsen , Ralph C. Smith