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We present a tail inequality for suprema of empirical processes generated by variables with finite $\psi_\alpha$ norms and apply it to some geometrically ergodic Markov chains to derive similar estimates for empirical processes of such…

Probability · Mathematics 2008-06-08 Radosław Adamczak

This paper develops a general concentration inequality for the suprema of empirical processes with dependent data. The concentration inequality is obtained by combining generic chaining with a coupling-based strategy. Our framework…

Econometrics · Economics 2026-02-23 Chiara Amorino , Christian Brownlees , Ankita Ghosh

If a random variable is not exponentially integrable, it is known that no concentration inequality holds for an infinite sequence of independent copies. Under mild conditions, we establish concentration inequalities for finite sequences of…

Probability · Mathematics 2007-05-23 Franck Barthe , Patrick Cattiaux , Cyril Roberto

Let $\mathcal{F}$ be a class of measurable functions on a measurable space $(S,\mathcal{S})$ with values in $[0,1]$ and let \[P_n=n^{-1}\sum_{i=1}^n\delta_{X_i}\] be the empirical measure based on an i.i.d. sample $(X_1,...,X_n)$ from a…

Probability · Mathematics 2016-08-16 Evarist Giné , Vladimir Koltchinskii

The purpose of this paper is to prove a weak convergence result for empirical processes indexed in general classes of functions and with an underlying $\alpha$-mixing sequence of random variables. In particular the uniformly boundedness…

Probability · Mathematics 2019-04-09 Maria Mohr

We prove a Bennett-type concentration bound for suprema of empirical processes based on sampling without replacement and a corresponding bound in the case of an arbitrary Hoeffding statistics. We improve on the previous results of such…

Probability · Mathematics 2023-01-10 Bartłomiej Polaczyk

Weak convergence of the empirical copula process indexed by a class of functions is established. Two scenarios are considered in which either some smoothness of these functions or smoothness of the underlying copula function is required. A…

Statistics Theory · Mathematics 2015-06-18 Dragan Radulovic , Marten Wegkamp , Yue Zhao

Weak convergence of the empirical copula process is shown to hold under the assumption that the first-order partial derivatives of the copula exist and are continuous on certain subsets of the unit hypercube. The assumption is…

Statistics Theory · Mathematics 2012-07-06 Johan Segers

This paper derives new maximal inequalities for empirical processes associated with separately exchangeable random arrays. For fixed index dimension $K\ge 1$, we establish a global maximal inequality bounding the $q$-th moment…

Econometrics · Economics 2025-03-12 Harold D. Chiang

We show two novel concentration inequalities for suprema of empirical processes when sampling without replacement, which both take the variance of the functions into account. While these inequalities may potentially have broad applications…

Machine Learning · Statistics 2014-11-27 Ilya Tolstikhin , Gilles Blanchard , Marius Kloft

We offer an umbrella type result which extends weak convergence of the classical empirical process on the line to that of more general processes indexed by functions of bounded variation. This extension is not contingent on the type of…

Statistics Theory · Mathematics 2017-09-14 Dragan Radulovic , Marten Wegkamp

We study the relative entropy between the empirical estimate of a discrete distribution and the true underlying distribution. If the minimum value of the probability mass function exceeds an $\alpha > 0$ (i.e. when the true underlying…

Statistics Theory · Mathematics 2021-09-21 Alankrita Bhatt , Ankit Pensia

In the past decades, weak convergence theory for stochastic processes has become a standard tool for analyzing the asymptotic properties of various statistics. Routinely, weak convergence is considered in the space of bounded functions…

Statistics Theory · Mathematics 2014-08-15 Axel Bücher , Johan Segers , Stanislav Volgushev

In this work we present concentration inequalities for the sum $S_n$ of independent integer-valued not necessary indentically distributed random variables, where each variable has tail function that can be bounded by some power function…

Probability · Mathematics 2019-03-07 Oleksii Omelchenko , Andrei A. Bulatov

We give a concentration inequality based on the premise that random variables take values within a particular region. The concentration inequality guarantees that, for any sequence of correlated random variables, the difference between the…

Probability · Mathematics 2020-02-21 Go Kato

This paper presents compact notations for concentration inequalities and convenient results to streamline probabilistic analysis. The new expressions describe the typical sizes and tails of random variables, allowing for simple operations…

Statistics Theory · Mathematics 2020-04-28 Kaizheng Wang

The empirical copula process plays a central role in the asymptotic analysis of many statistical procedures which are based on copulas or ranks. Among other applications, results regarding its weak convergence can be used to develop…

Statistics Theory · Mathematics 2014-11-24 Axel Bücher , Betina Berghaus , Stanislav Volgushev

In this paper we revisit Talagrand's proof of concentration inequality for empirical processes. We give a different shorter proof of the main technical lemma that guarantees the existence of a certain kernel. Our proof provides the almost…

Probability · Mathematics 2021-04-13 Dmitry Panchenko

We derive an upper bound for the mean of the supremum of the empirical process indexed by a class of functions that are known to have variance bounded by a small constant $\delta$. The bound is expressed in the uniform entropy integral of…

Statistics Theory · Mathematics 2010-12-30 Aad van der Vaart , Jon A. Wellner

In this note we derive a sharp concentration inequality for the supremum of a smooth random field over a finite dimensional set. It is shown that this supremum can be bounded with high probability by the value of the field at some…

Statistics Theory · Mathematics 2013-07-08 Denis Belomestny , Vladimir Spokoiny
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