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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 compare expected star discrepancy under jittered sampling with simple random sampling, and the strong partition principle for the star discrepancy is proved.

Probability · Mathematics 2023-01-24 Jun Xian , Xiaoda Xu

We investigate the expected star discrepancy under a newly designed class of convex equivolume partition models. The main contributions are two-fold. First, we establish a strong partition principle for the star discrepancy, showing that…

Probability · Mathematics 2026-01-09 Xiaoda Xu , Jun Xian

We study the expected star discrepancy under a newly designed class of non-equal volume partitions. The main contributions are twofold. First, we establish a strong partition principle for the star discrepancy, showing that our newly…

Machine Learning · Statistics 2026-03-10 Xiaoda Xu

In this paper, we consider the upper bound of the probabilistic star discrepancy based on Hilbert space filling curve sampling. This problem originates from the multivariate integral approximation, but the main result removes the strict…

Statistics Theory · Mathematics 2023-04-20 Jun Xian , Xiaoda Xu

We introduce a class of convex equivolume partitions. Expected $L_2-$discrepancy are discussed under these partitions. There are two main results. First, under this kind of partitions, we generate random point sets with smaller expected…

Statistics Theory · Mathematics 2022-04-20 Jun Xian , Xiaoda Xu

We extend the notion of jittered sampling to arbitrary partitions and study the discrepancy of the related point sets. Let $\mathbf{\Omega}=(\Omega_1,\ldots,\Omega_N)$ be a partition of $[0,1]^d$ and let the $i$th point in $\mathcal{P}$ be…

Statistics Theory · Mathematics 2021-02-01 Markus Kiderlen , Florian Pausinger

For $m, d \in {\mathbb N}$, a jittered sampling point set $P$ having $N = m^d$ points in $[0,1)^d$ is constructed by partitioning the unit cube $[0,1)^d$ into $m^d$ axis-aligned cubes of equal size and then placing one point independently…

Numerical Analysis · Mathematics 2022-06-13 Benjamin Doerr

We study the expected $ L_2-$discrepancy under two classes of partitions, explicit and exact formulas are derived respectively. These results attain better expected $L_2-$discrepancy formulas than jittered sampling.

Computation · Statistics 2023-03-13 Jun Xian , Xiaoda Xu

We study the discrepancy of jittered sampling sets: such a set $\mathcal{P} \subset [0,1]^d$ is generated for fixed $m \in \mathbb{N}$ by partitioning $[0,1]^d$ into $m^d$ axis aligned cubes of equal measure and placing a random point…

Numerical Analysis · Mathematics 2015-10-02 Florian Pausinger , Stefan Steinerberger

We study the expected $\mathcal{L}_2$-discrepancy of stratified samples generated from special equi-volume partitions of the unit square. The partitions are defined via parallel lines that are all orthogonal to the diagonal of the square.…

Number Theory · Mathematics 2024-01-02 Florian Pausinger

In this paper we propose an acceptance-rejection sampler using stratified inputs as diver sequence. We estimate the discrepancy of the points generated by this algorithm. First we show an upper bound on the star discrepancy of order…

Computation · Statistics 2014-08-11 Houying Zhu , Josef Dick

For $m, d \in \mathbb{N}$, a jittered sample of $N=m^d$ points can be constructed by partitioning $[0,1]^d$ into $m^d$ axis-aligned equivolume boxes and placing one point independently and uniformly at random inside each box. We utilise a…

Probability · Mathematics 2022-09-13 Nathan Kirk , Florian Pausinger

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

This paper studies the expected $L_p$-discrepancy ($2 \leq p < \infty$) for stratified sampling schemes under importance sampling. We introduce a parametric family of equivolume partitions $\Omega_{\theta,\sim}$ and leverage recent exact…

Numerical Analysis · Mathematics 2026-01-09 Xiaoda Xu

We prove that classical jittered sampling of the $d$-dimensional unit cube does not yield the smallest expected $\mathcal{L}_2$-discrepancy among all stratified samples with $N=m^d$ points. Our counterexample can be given explicitly and…

Number Theory · Mathematics 2021-10-20 Markus Kiderlen , Florian Pausinger

We provide probabilistic lower bounds for the star discrepancy of Latin hypercube samples. These bounds are sharp in the sense that they match the recent probabilistic upper bounds for the star discrepancy of Latin hypercube samples proved…

Numerical Analysis · Mathematics 2021-09-21 Benjamin Doerr , Carola Doerr , Michael Gnewuch

Jittered Sampling is a refinement of the classical Monte Carlo sampling method. Instead of picking $n$ points randomly from $[0,1]^2$, one partitions the unit square into $n$ regions of equal measure and then chooses a point randomly from…

Numerical Analysis · Mathematics 2017-04-20 Florian Pausinger , Manas Rachh , Stefan Steinerberger

Classical jittered sampling partitions $[0,1]^d$ into $m^d$ cubes for a positive integer $m$ and randomly places a point inside each of them, providing a point set of size $N=m^d$ with small discrepancy. The aim of this note is to provide a…

Combinatorics · Mathematics 2023-06-30 Francois Clement , Nathan Kirk , Florian Pausinger

We consider a certain equidistributed sequence of rational numbers constructed from the primes. In particular, we determine the sharp convergence rate for the star discrepancy of said sequence. Our arguments are based on well-known…

Number Theory · Mathematics 2021-07-29 Martin Lind
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