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A central problem in Binary Hypothesis Testing (BHT) is to determine the optimal tradeoff between the Type I error (referred to as false alarm) and Type II (referred to as miss) error. In this context, the exponential rate of convergence of…

Information Theory · Computer Science 2021-11-29 Sebastian Espinosa , Jorge F. Silva , Pablo Piantanida

The statistical measure of spatial inhomogeneity for n points placed in chi cells each of size kxk is generalized to incorporate finite size objects like black pixels for binary patterns of size LxL. As a function of length scale k, the…

Statistical Mechanics · Physics 2009-11-11 Ryszard Piasecki

A classical problem in statistics is estimating the expected coverage of a sample, which has had applications in gene expression, microbial ecology, optimization, and even numismatics. Here we consider a related extension of this problem to…

Statistics Theory · Mathematics 2013-02-11 Jerrad Hampton , Manuel E. Lladser

We develop a notion of sampling, called \emph{generic sampling}, for the context of global Keisler measures where the standard product is replaced by the Morley product. Choosing a point randomly in this space with respect to our…

Logic · Mathematics 2026-03-26 Kyle Gannon , James E. Hanson

The paper provides a simpler method for proving a delicate inequality that was used by Achlioptis and Naor to establish asymptotic concentration for chromatic numbers of Erdos-Renyi random graphs. The simplifications come from two new…

Discrete Mathematics · Computer Science 2011-07-20 John Hartigan , David Pollard , Sekhar Tatikonda

We give a nearly-optimal algorithm for testing uniformity of distributions supported on $\{-1,1\}^n$, which makes $\tilde O (\sqrt{n}/\varepsilon^2)$ queries to a subcube conditional sampling oracle (Bhattacharyya and Chakraborty (2018)).…

Data Structures and Algorithms · Computer Science 2021-02-08 Clément L. Canonne , Xi Chen , Gautam Kamath , Amit Levi , Erik Waingarten

For high-dimensional small sample size data, Hotelling's T2 test is not applicable for testing mean vectors due to the singularity problem in the sample covariance matrix. To overcome the problem, there are three main approaches in the…

Methodology · Statistics 2020-03-11 Zongliang Hu , Tiejun Tong , Marc G. Genton

In this paper, we consider the thin obstacle problem in $\mathbb{R}^2$ with data at infinity. We first prove the existence and uniqueness of it. Then we show that its symmetric solutions are actually half-space solutions. Our results are…

Analysis of PDEs · Mathematics 2022-01-06 Runcao Lyu , Zikai Ye

We obtain asymptotic expansions for local probabilities of partial sums for uniformly bounded independent but not necessarily identically distributed integer-valued random variables. The expansions involve products of polynomials and…

Probability · Mathematics 2020-12-02 Dmitry Dolgopyat , Yeor Hafouta

A homemorphism between domains in $\mathbb R^n$, $n\ge 2$ is quasiconformal, with its intricate analytic and geometric consequences, if the (pointwise) linear dilatation -- a purely metric quantity -- is uniformly bounded. Gehring proved…

Functional Analysis · Mathematics 2026-04-01 Behnam Esmayli , Pekka Koskela , Khanh Nguyen

Statistical methodology plays a crucial role in drug regulation. Decisions by the FDA or EMA are typically made based on multiple primary studies testing the same medical product, where the two-trials rule is the standard requirement,…

Methodology · Statistics 2022-11-08 Leonhard Held

Testing whether two multivariate samples exhibit the same extremal behavior is an important problem in various fields including environmental and climate sciences. While several ad-hoc approaches exist in the literature, they often lack…

Statistics Theory · Mathematics 2026-02-03 Sebastian Engelke , Philippe Naveau , Chen Zhou

We consider the problem of testing a null hypothesis defined by equality and inequality constraints on a statistical parameter. Testing such hypotheses can be challenging because the number of relevant constraints may be on the same order…

Methodology · Statistics 2024-02-19 Nils Sturma , Mathias Drton , Dennis Leung

In this paper we first make and discuss a conjecture concerning Newtonian potentials in Euclidean n space which have all their mass on the unit sphere about the origin, and are normalized to be one at the origin. The conjecture essentially…

Classical Analysis and ODEs · Mathematics 2024-11-05 John Lewis

We study a variant of the simple hypothesis testing problem where observed samples do not necessarily come from either of the specified distributions, but rather from a close variant of them. In this setting, we require a test that is…

Statistics Theory · Mathematics 2026-04-21 Eeshan Modak , Sivaraman Balakrishnan , Ananda Theertha Suresh

We investigate the limiting behavior of sample central moments, examining the special cases where the limiting (as the sample size tends to infinity) distribution is degenerate. Parent (non-degenerate) distributions with this property are…

Statistics Theory · Mathematics 2018-06-07 Georgios Afendras , Nickos Papadatos , Violetta Piperigou

We propose a two-sample test for large-dimensional covariance matrices in generalized elliptical models. The test statistic is based on a U-statistic estimator of the squared Frobenius norm of the difference between the two population…

Statistics Theory · Mathematics 2025-07-04 Nina Dörnemann

This paper tackles the issue of establishing a lower-bound on the asymptotic ratio of survival probabilities between two different initial conditions, asymptotically in time for a given Markov process with extinction. Such a comparison is a…

Probability · Mathematics 2023-05-12 Aurélien Velleret

The family of U-statistics plays a fundamental role in statistics. This paper proves a novel exponential inequality for U-statistics under the time series setting. Explicit mixing conditions are given for guaranteeing fast convergence, the…

Statistics Theory · Mathematics 2016-11-16 Fang Han

Many popular dimensionality reduction procedures have out-of-sample extensions, which allow a practitioner to apply a learned embedding to observations not seen in the initial training sample. In this work, we consider the problem of…

Machine Learning · Statistics 2018-02-20 Keith Levin , Farbod Roosta-Khorasani , Michael W. Mahoney , Carey E. Priebe