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For Kolmogorov test we find natural conditions of uniform consistency of sets of alternatives approaching to hypothesis. Sets of alternatives can be defined both in terms of distribution functions and in terms of densities.

Statistics Theory · Mathematics 2022-11-28 Mikhail Ermakov

In this paper, we study the convergence of the spectral embeddings obtained from the leading eigenvectors of certain similarity matrices to their population counterparts. We opt to study this convergence in a uniform (instead of average)…

Statistics Theory · Mathematics 2023-04-26 Ruofei Zhao , Songkai Xue , Yuekai Sun

This paper derives normal approximation results for subgraph counts written as multiparameter stochastic integrals in a random-connection model based on a Poisson point process. By combinatorial arguments we express the cumulants of general…

Probability · Mathematics 2025-11-11 Qingwei Liu , Nicolas Privault

Robust statistical inference often faces a severe computational-statistical gap when dealing with complex parameter spaces. We investigate minimax signal detection in the Gaussian sequence model under strong $\epsilon$-contamination, where…

Statistics Theory · Mathematics 2026-05-13 Yikun Li , Matey Neykov

Uniform and nonuniform Berry--Esseen (BE) bounds of optimal orders on the closeness to normality for general abstract nonlinear statistics are given, which are then used to obtain optimal bounds on the rate of convergence in the delta…

Statistics Theory · Mathematics 2017-01-17 Iosif Pinelis , Raymond Molzon

We consider uniform approximations by trigonometric polynomials. The aim of the paper is to obtain good estimates of the Jackson--Stechkin constants $J_m$. We prove that $ J_m \le C 2^{-m+5/2\log_2m}$. Our proof is based on the difference…

Classical Analysis and ODEs · Mathematics 2007-05-23 Y. Kryakin

In this paper, a simplified second-order Gaussian Poincar\'e inequality for normal approximation of functionals over infinitely many Rademacher random variables is derived. It is based on a new bound for the Kolmogorov distance between a…

Probability · Mathematics 2023-01-31 Peter Eichelsbacher , Benedikt Rednoß , Christoph Thäle , Guangqu Zheng

In the context of nonparametric regression models with one-sided errors, we consider parametric transformations of the response variable in order to obtain independence between the errors and the covariates. We focus in this paper on…

Statistics Theory · Mathematics 2019-01-31 Natalie Neumeyer , Leonie Selk , Charles Tillier

We establish presumably optimal rates of normal convergence with respect to the Kolmogorov distance for a large class of geometric functionals of marked Poisson and binomial point processes on general metric spaces. The rates are valid…

Probability · Mathematics 2017-02-03 Raphaël Lachièze-Rey , Matthias Schulte , J. E. Yukich

In this article, we obtain explicit bounds on the uniform distance between the cumulative distribution function of a standardized sum $S_n$ of $n$ independent centered random variables with moments of order four and its first-order…

Probability · Mathematics 2025-07-30 Alexis Derumigny , Lucas Girard , Yannick Guyonvarch

Under the Kolmogorov--Smirnov metric, an upper bound on the rate of convergence to the Gaussian distribution is obtained for linear statistics of the matrix ensembles in the case of the Gaussian, Laguerre, and Jacobi weights. The main lemma…

Probability · Mathematics 2020-06-16 Sergey Berezin , Alexander I. Bufetov

We present a simple solution to a question posed by Candes, Romberg and Tao on the uniform uncertainty principle for Bernoulli random matrices. More precisely, we show that a rectangular k*n random subgaussian matrix (with k < n) has the…

Statistics Theory · Mathematics 2007-06-13 Shahar Mendelson , Alain Pajor , Nicole Tomczak-Jaegermann

We study approximation theorems for the Euler characteristic of the Vietoris-Rips and Cech filtration. The filtration is obtained from a Poisson or binomial sampling scheme in the critical regime. We apply our results to the smooth…

Probability · Mathematics 2021-09-21 Johannes Krebs , Benjamin Roycraft , Wolfgang Polonik

The Shapley-Folkman theorem shows that Minkowski averages of uniformly bounded sets tend to be convex when the number of terms in the sum becomes much larger than the ambient dimension. In optimization, Aubin and Ekeland [1976] show that…

Optimization and Control · Mathematics 2019-07-02 Thomas Kerdreux , Igor Colin , Alexandre d'Aspremont

In the literature of high-dimensional central limit theorems, there is a gap between results for general limiting correlation matrix $\Sigma$ and the strongly non-degenerate case. For the general case where $\Sigma$ may be degenerate, under…

Probability · Mathematics 2023-05-30 Xiao Fang , Yuta Koike , Song-Hao Liu , Yi-Kun Zhao

In this paper we give a lower bound on the waist of the unit sphere of a uniformly convex normed space by using the localization technique in codimension greater than one and a strong version of the Borsuk-Ulam theorem. The tools used in…

Metric Geometry · Mathematics 2019-02-20 Yashar Memarian

We propose a novel small time approximation for the solution to the Zakai equation from nonlinear filtering theory. We prove that the unnormalized filtering density is well described over short time intervals by the solution of a…

Probability · Mathematics 2021-05-27 Alberto Lanconelli , Ramiro Scorolli

In Stein's method, the exchangeable pair approach is commonly used to estimate the approximation errors in normal approximation. In this paper, we establish a Cram\'er-type moderate deviation theorem of normal approximation for unbounded…

Probability · Mathematics 2022-09-26 Zhuo-Song Zhang

For integer valued random variables, the translated Poisson distributions form a flexible family for approximation in total variation, in much the same way that the normal family is used for approximation in Kolmogorov distance. Using the…

Probability · Mathematics 2016-12-26 A. D. Barbour , Malwina J. Luczak , Aihua Xia

Let $\mathbf X=(X_{jk})$ denote a Hermitian random matrix with entries $X_{jk}$, which are independent for $1\le j\le k$. We consider the rate of convergence of the empirical spectral distribution function of the matrix $\mathbf X$ to the…

Probability · Mathematics 2013-10-29 Friedrich Götze , Alexander Tikhomirov