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The bijectivity of the mapping, which is represented as expectation, from a family of Gaussian measures parametrized by linear combinations of Dirac measures to the space of classical reflectionless potentials is shown. It is also shown…

Probability · Mathematics 2007-05-23 Setsuo Taniguchi

We study the problem of generalized uniformity testing \cite{BC17} of a discrete probability distribution: Given samples from a probability distribution $p$ over an {\em unknown} discrete domain $\mathbf{\Omega}$, we want to distinguish,…

Data Structures and Algorithms · Computer Science 2017-09-08 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

Consider the boundary $\partial \mathbb D$ of the Brownian disk $\mathbb D$ as a metric space by endowing it with the (restriction of the) metric of $\mathbb D$. We show that the uniform measure on $\partial \mathbb D$ coincides with the…

Probability · Mathematics 2024-11-27 Alexis Metz--Donnadieu

We obtain an elementary invariance principle for multi-dimensional Brownian sheet where the underlying random fields are not necessarily independent or stationary. Possible applications include unit-root tests for spatial as well as panel…

Probability · Mathematics 2019-10-08 Michael C. Tseng

We propose a projection-based class of uniformity tests on the hypersphere using statistics that integrate, along all possible directions, the weighted quadratic discrepancy between the empirical cumulative distribution function of the…

In this article, we propose a new class of consistent tests for $p$-variate normality. These tests are based on the characterization of the standard multivariate normal distribution, that the Hessian of the corresponding cumulant generating…

Methodology · Statistics 2023-03-22 Kwun Chuen Gary Chan , Hok Kan Ling , Chuan-Fa Tang , Sheung Chi Phillip Yam

Data uniformity is a concept associated with several semantic data characteristics such as lack of features, correlation and sample bias. This article introduces a novel measure to assess data uniformity and detect uniform pointsets on…

Computational Geometry · Computer Science 2020-04-14 Panagiotis Sidiropoulos

We show that, under certain natural assumptions, large random plane bipartite maps with a boundary converge after rescaling to a one-parameter family ($\mathrm{BD}_L$, $0 < L < \infty$) of random metric spaces homeomorphic to the closed…

Probability · Mathematics 2016-02-12 Jérémie Bettinelli , Gregory Miermont

The paths of Brownian motion have been widely studied in the recent years relatively in Besov spaces $B_{p, \infty}^\a$. The results are the same as to the Brownian bridge. In fact these regularities properties are established in some…

Probability · Mathematics 2015-03-13 Gane Samb Lo , Ahmadou Bamba Sow

The problem of testing changes in covariance has received increasing attention in recent years, especially in the context of high-dimensional testing. A number of approaches have been proposed, all limited to the two-sample problem and…

Methodology · Statistics 2016-09-06 Yi-Hui Zhou

The main message in this paper is that there are surprisingly many different Brownian bridges, some of them - familiar, some of them - less familiar. Many of these Brownian bridges are very close to Brownian motions. Somewhat loosely…

Statistics Theory · Mathematics 2016-01-08 Estate Khmaladze

We show that simple explicit formulas can be obtained for several relevant quantities related to the laws of the uniformly sampled Brownian bridge, Brownian meander and three dimensional Bessel process. To prove such results, we use the…

Probability · Mathematics 2013-11-11 Mathieu Rosenbaum , Marc Yor

We provide a new construction of the Brownian disks, which have been defined by Bettinelli and Miermont as scaling limits of quadrangulations with a boundary when the boundary size tends to infinity. Our method is very similar to the…

Probability · Mathematics 2017-10-23 Jean-François Le Gall

Many multiple testing procedures make use of the p-values from the individual pairs of hypothesis tests, and are valid if the p-value statistics are independent and uniformly distributed under the null hypotheses. However, it has recently…

Methodology · Statistics 2011-08-25 Joshua D. Habiger , Edsel A. Pena

Given a sample from a multivariate distribution $F$, the uniform random variates generated independently and rearranged in the order specified by the componentwise ranks of the original sample look like a sample from the copula of $F$. This…

Statistics Theory · Mathematics 2016-11-21 Johan Segers , Masaaki Sibuya , Hideatsu Tsukahara

Uniform convergence of empirical norms - empirical measures of squared functions - is a topic which has received considerable attention in the literature on empirical processes. The results are relevant as empirical norms occur due to…

Statistics Theory · Mathematics 2013-10-22 Sara van de Geer

Testing hypothesis of independence between two random elements on a joint alphabet is a fundamental exercise in statistics. Pearson's chi-squared test is an effective test for such a situation when the contingency table is relatively small.…

Statistics Theory · Mathematics 2025-03-19 Jialin Zhang , Zhiyi Zhang

This article investigates, by probabilistic methods, various geometric questions on B_p^n, the unit ball of \ell_p^n. We propose realizations in terms of independent random variables of several distributions on B_p^n, including the…

Probability · Mathematics 2007-05-23 Franck Barthe , Olivier Guedon , Shahar Mendelson , Assaf Naor

We consider the model of the Brownian plane, which is a pointed non-compact random metric space with the topology of the complex plane. The Brownian plane can be obtained as the scaling limit in distribution of the uniform infinite planar…

Probability · Mathematics 2021-05-14 Armand Riera

This paper describes a recursive estimation procedure for multivariate binary densities (probability distributions of vectors of Bernoulli random variables) using orthogonal expansions. For $d$ covariates, there are $2^d$ basis coefficients…

Statistics Theory · Mathematics 2012-12-03 Maxim Raginsky , Jorge Silva , Svetlana Lazebnik , Rebecca Willett