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The Landau-Pollak uncertainty relation treats a pair of rank one projection valued measures and imposes a restriction on their probability distributions. It gives a nontrivial bound for summation of their maximum values. We give a…

Quantum Physics · Physics 2008-10-30 Takayuki Miyadera , Hideki Imai

This paper describes prediction methods for the number of future events from a population of units associated with an on-going time-to-event process. Examples include the prediction of warranty returns and the prediction of the number of…

Methodology · Statistics 2020-08-10 Qinglong Tian , Fanqi Meng , Daniel J. Nordman , William Q. Meeker

In this note, we give an explicit expression for the quantile of a mixture of two random variables. We carefully examine all possible cases of discrete and continuous variables with possibly unbounded support. The result is useful for…

Other Statistics · Statistics 2014-11-19 Carole Bernard , Steven Vanduffel

Estimating mutual information (MI) is a fundamental yet challenging task in data science and machine learning. This work proposes a new estimator for mutual information. Our main discovery is that a preliminary estimate of the data…

Machine Learning · Computer Science 2024-08-20 Yanzhi Chen , Zijing Ou , Adrian Weller , Yingzhen Li

This is a survey of results on random group presentations, and on random subgroups of certain fixed groups. Being a survey, this paper does not contain new results, but it offers a synthetic view of a part of this very active field of…

Group Theory · Mathematics 2021-11-19 Frédérique Bassino , Cyril Nicaud , Pascal Weil

A well-known technique in estimating probabilities of rare events in general and in information theory in particular (used, e.g., in the sphere-packing bound), is that of finding a reference probability measure under which the event of…

Information Theory · Computer Science 2014-12-23 Rami Atar , Neri Merhav

Aggregated predictors are obtained by making a set of basic predictors vote according to some weights, that is, to some probability distribution. Randomized predictors are obtained by sampling in a set of basic predictors, according to some…

Machine Learning · Statistics 2025-03-03 Pierre Alquier

We consider importance sampling to estimate the probability $\mu$ of a union of $J$ rare events $H_j$ defined by a random variable $\boldsymbol{x}$. The sampler we study has been used in spatial statistics, genomics and combinatorics going…

Computation · Statistics 2018-12-20 Art B. Owen , Yury Maximov , Michael Chertkov

Consider a set P of N random points on the unit sphere of dimension $d-1$, and the symmetrized set S = P union (-P). The halving polyhedron of S is defined as the convex hull of the set of centroids of N distinct points in S. We prove that…

Computational Geometry · Computer Science 2014-04-25 Quentin Mérigot

Predicting the winner of an election is of importance to multiple stakeholders. To formulate the problem, we consider an independent sequence of categorical data with a finite number of possible outcomes in each. The data is assumed to be…

Applications · Statistics 2024-10-17 Soudeep Deb , Rishideep Roy , Shubhabrata Das

This paper presents formulae for calculation of cumulative probability of effect made by blast fragments. Analysis with Mott distribution, discrete fragment enumeration, spatial non-uniformity, numerical issues, and a generalisation for a…

General Physics · Physics 2013-04-09 Oleg Mazonka

Sums of independent, bounded random variables concentrate around their expectation approximately as well a Gaussian of the same variance. Well known results of this form include the Bernstein, Hoeffding, and Chernoff inequalities and many…

Discrete Mathematics · Computer Science 2017-04-25 Thomas Steinke , Jonathan Ullman

We provide novel bounds on average treatment effects (on the treated) that are valid under an unconfoundedness assumption. Our bounds are designed to be robust in challenging situations, for example, when the conditioning variables take on…

Econometrics · Economics 2026-05-12 Sokbae Lee , Martin Weidner

The theory of belief functions manages uncertainty and also proposes a set of combination rules to aggregate opinions of several sources. Some combination rules mix evidential information where sources are independent; other rules are…

Artificial Intelligence · Computer Science 2015-03-18 Mouna Chebbah , Arnaud Martin , Boutheina Ben Yaghlane

We prove lower bounds on the error of any estimator for the mean of a real probability distribution under the knowledge that the distribution belongs to a given set. We apply these lower bounds both to parametric and nonparametric…

Statistics Theory · Mathematics 2024-03-05 Rémy Degenne , Timothée Mathieu

By combining a bound on the absolute value of the difference of mutual information between two joint probablity distributions with a fixed variational distance, and a bound on the probability of a maximal deviation in variational distance…

Information Theory · Computer Science 2013-01-29 A. G. Stefani , J. B. Huber , C. Jardin , H. Sticht

We investigate the bounding problem of causal effects in experimental studies in which the outcome is truncated by death, meaning that the subject dies before the outcome can be measured. Causal effects cannot be point identified without…

Methodology · Statistics 2024-04-29 Aixian Chen , Xia Cui , Guangren Yang

A classical statistical inequality is used to show that the distance covariance of two bounded random vectors is bounded from above by a simple function of the dimensionality and the bounds of the random vectors. Two special cases that…

Probability · Mathematics 2023-06-30 John Çamkıran

Spread of information in crowd is analysed in terms of directed percolation in two-dimensional spatial network. We investigate the case when the information transmitted can be incomplete or damaged. The results indicate that for small or…

Physics and Society · Physics 2011-04-26 Krzysztof Malarz , Vikas Chandra , Eve Mitleton-Kelly , Krzysztof Kulakowski

Coherent lower previsions are general probabilistic models allowing incompletely specified probability distributions. However, for complete description of a coherent lower prevision -- even on finite underlying sample spaces -- an infinite…

Probability · Mathematics 2022-09-29 Damjan Škulj