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We derive an asymptotic expansion for the distribution of a compound sum of independent random variables, all having the same light-tailed subexponential distribution. The examples of a Poisson and geometric number of summands serve as an…

Probability · Mathematics 2007-05-23 Ph . Barbe , W. P. McCormick , C. Zhang

We present a universal concentration bound for sums of random variables under arbitrary dependence, and we prove that it is asymptotically optimal for broad families of marginals admitting a uniform integrable tail-quantile envelope. The…

Probability · Mathematics 2026-03-05 Cosme Louart , Sicheng Tan

The method to derive uniform bounds with Gaussian and Rademacher complexities is extended to the case where the sample average is replaced by a nonlinear statistic. Tight bounds are obtained for U-statistics, smoothened L-statistics and…

Statistics Theory · Mathematics 2019-05-13 Andreas Maurer , Massimiliano Pontil

We modify the classical Bernstein's inequality for the sums of independent centered random variables (r.v.) in the terms of relative tails or moments. We built also some examples in order to show the exactness of offered results.

Probability · Mathematics 2022-06-03 M. R. Formica , E. Ostrovsky , L. Sirota

For dynamical systems modeled by a Young tower with exponential tails, we prove an exponential concentration inequality for all separately Lipschitz observables of n variables. When tails are polynomial, we prove polynomial concentration…

Dynamical Systems · Mathematics 2015-06-03 Jean-René Chazottes , Sebastien Gouezel

We present sharp tail asymptotics for the density and the distribution function of linear combinations of correlated log-normal random variables, that is, exponentials of components of a correlated Gaussian vector. The asymptotic behavior…

Probability · Mathematics 2016-01-07 Archil Gulisashvili , Peter Tankov

Generalized likelihoods are commonly used to obtain consistent estimators with attractive computational and robustness properties. Formally, any generalized likelihood can be used to define a generalized posterior distribution, but an…

Statistics Theory · Mathematics 2021-05-04 Jeffrey W. Miller

In this document we achieve exact and asymptotic enumeration of words, compositions over a finite group, and/or integer compositions characterized by local restrictions and, separately, subsequence pattern avoidance. We also count…

Combinatorics · Mathematics 2019-04-19 Andrew MacFie

We give sufficient conditions for the asymptotic normality of linear combinations of order statistics (L-statistics) in the case of simple random samples without replacement. In the first case, restrictions are imposed on the weights of…

Statistics Theory · Mathematics 2012-04-11 Andrius Čiginas

Sample size criteria are often expressed in terms of the concentration of the posterior density, as controlled by some sort of error bound. Since this is done pre-experimentally, one can regard the posterior density as a function of the…

Statistics Theory · Mathematics 2007-06-13 B. Clarke , Ao Yuan

This note describes non-asymptotic variance and tail bounds for order statistics of samples of independent identically distributed random variables. Those bounds are checked to be asymptotically tight when the sampling distribution belongs…

Probability · Mathematics 2012-11-05 Stephane Boucheron , Maud Thomas

In this paper we present a tail inequality for the maximum of partial sums of a weakly dependent sequence of random variables that are not necessarily bounded. The class considered includes geometrically and subgeometrically strongly mixing…

Probability · Mathematics 2009-02-04 Florence Merlevède , Magda Peligrad , Emmanuel Rio

In the paper we propose some new class of functions which is used to construct tail index estimators. Functions from this new class is non-monotone in general, but presents a product of two monotone functions: the power function and the…

Statistics Theory · Mathematics 2015-01-06 Vygantas Paulauskas , Marijus Vaičiulis

Asymptotic notations are heavily used while analysing runtimes of algorithms. Present paper argues that some of these usages are non trivial, therefore incurring errors in communication of ideas. After careful reconsidera- tion of the…

Computational Complexity · Computer Science 2015-10-20 Nabarun Mondal , Partha P. Ghosh

We investigate quantitative implications of the notion of log-concavity through a probabilistic interpretation. In particular, we derive concentration inequalities, moment and entropy bounds for random variables satisfying a precise degree…

Probability · Mathematics 2026-02-19 Arnaud Marsiglietti , James Melbourne

In this note we prove bounds on the upper and lower probability tails of sums of independent geometric or exponentially distributed random variables. We also prove negative results showing that our established tail bounds are asymptotically…

Statistics Theory · Mathematics 2019-02-11 Yaonan Jin , Yingkai Li , Yining Wang , Yuan Zhou

This paper derives exponential tail bounds and polynomial moment inequalities for the spectral norm deviation of a random matrix from its mean value. The argument depends on a matrix extension of Stein's method of exchangeable pairs for…

Probability · Mathematics 2013-05-06 Daniel Paulin , Lester Mackey , Joel A. Tropp

These informal notes are concerned with sums and averages in various situations in analysis.

Classical Analysis and ODEs · Mathematics 2010-08-17 Stephen Semmes

The routine definitions of both entropy, and differential entropy show inconsistencies that make them not reciprocally coherent. We propose a few possible modifications of these quantities so that 1) they no longer show incongruities, 2)…

Information Theory · Computer Science 2014-08-08 Nicola Cufaro Petroni

We prove concentration inequalities for functions of independent random variables {under} sub-gaussian and sub-exponential conditions. The utility of the inequalities is demonstrated by an extension of the now classical method of Rademacher…

Probability · Mathematics 2021-06-24 Andreas Maurer , Massimiliano Pontil