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The classical Bayesian posterior arises naturally as the unique solution of several different optimization problems, without the necessity of interpreting data as conditional probabilities and then using Bayes' Theorem. For example, the…

Statistics Theory · Mathematics 2012-03-02 Theodore P. Hill , Marco Dall'Aglio

Motivated by a recent random pipe dream model, we study a family of probability distributions on \(S_n\) arising from Bott--Samelson varieties over finite fields. More precisely, for a word \(R\), we consider the Bott--Samelson map…

Combinatorics · Mathematics 2026-05-26 Jingqi Li , Haorun Yin , Wenbin Yu , Shixuan Zeng

Quantile aggregation with dependence uncertainty has a long history in probability theory with wide applications in finance, risk management, statistics, and operations research. Using a recent result on inf-convolution of quantile-based…

Risk Management · Quantitative Finance 2024-09-09 Jose Blanchet , Henry Lam , Yang Liu , Ruodu Wang

The data of a physical experiment can be represented as a presheaf of probability distributions. A striking feature of quantum theory is that those probability distributions obtained in quantum mechanical experiments do not always admit a…

Category Theory · Mathematics 2022-11-02 Aziz Kharoof , Cihan Okay

Real space condensation is known to occur in stochastic models of mass transport in the regime in which the globally conserved mass density is greater than a critical value. It has been shown within models with factorised stationary states…

Statistical Mechanics · Physics 2014-11-04 Juraj Szavits-Nossan , Martin R. Evans , Satya N. Majumdar

Constrained quantization for a Borel probability measure refers to the idea of estimating a given probability by a discrete probability with a finite number of supporting points lying on a specific set. The specific set is known as the…

The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus to make an approximation of a continuous…

Probability · Mathematics 2022-08-23 Joseph Rosenblatt , Mrinal Kanti Roychowdhury

We develop a unified approach to the problem of clustering in the three different fields of applications, as indicated in the title the paper. The approach is based on Khintchine's probabilistic method that grew out of the Darwin-Fawler…

Probability · Mathematics 2007-06-13 Gregory Freiman , Boris Granovsky

We consider the following frustrated optimization problem: given a prior probability distribution $q$, find the distribution $p$ minimizing the relative entropy with respect to $q$ such that $\textrm{mean}(p)$ is fixed and large. We show…

Statistical Mechanics · Physics 2016-12-06 Matteo Smerlak

From a new class of q-deformed coherent states we introduce a generalization of the Euler probability distribution for which the main statistical parameters are obtained explicitly. As application, we discuss the corresponding photon…

Mathematical Physics · Physics 2021-07-14 Zouhair Mouayn , Othmane El moize

Quantization for a probability distribution refers to the idea of estimating a given probability by a discrete probability supported by a finite set. In this article, we consider a probability distribution generated by an infinite system of…

Dynamical Systems · Mathematics 2022-04-26 Dogan Comez , Mrinal Kanti Roychowdhury

This paper proposes another constant that can be associated with Fibonacci sequence. In this work, we look at the probability distributions generated by the linear convolution of Fibonacci sequence with itself, and the linear convolution of…

Probability · Mathematics 2010-05-10 Arulalan Rajan , Jamadagni , Vittal Rao , Ashok Rao

We study the distribution of spacings between squares modulo q, where q is square-free and highly composite, in the limit as the number of prime factors of q goes to infinity. We show that all correlation functions are Poissonian, which…

Number Theory · Mathematics 2007-05-23 P. Kurlberg , Z. Rudnick

This study focuses on statistical inference for compound models of the form $X=\xi_1+\ldots+\xi_N$, where $N$ is a random variable denoting the count of summands, which are independent and identically distributed (i.i.d.) random variables…

Statistics Theory · Mathematics 2025-07-22 Denis Belomestny , Ekaterina Morozova , Vladimir Panov

We study the Euler-Frobenius numbers, a generalization of the Eulerian numbers, and the probability distribution obtained by normalizing them. This distribution can be obtained by rounding a sum of independent uniform random variables; this…

Probability · Mathematics 2013-05-17 Svante Janson

In this paper, some general properties of Shannon information measures are investigated over sets of probability distributions with restricted marginals. Certain optimization problems associated with these functionals are shown to be…

Information Theory · Computer Science 2020-08-13 Mladen Kovačević , Ivan Stanojević , Vojin Šenk

Let $X$ be a second countable locally compact Abelian group containing no subgroup topologically isomorphic to the circle group $\mathbb{T}$. Let $\mu$ be a probability distribution on $X$ such that its characteristic function $\hat\mu(y)$…

Probability · Mathematics 2013-09-27 G. Feldman , P. Graczyk

It is shown that (i) all entangled states can be mapped by single-copy measurements into probability distributions containing secret correlations, and (ii) if a probability distribution obtained from a quantum state contains secret…

Quantum Physics · Physics 2009-11-10 Antonio Acin , Nicolas Gisin

We consider a component of the word statistics known as clump; starting from a finite set of words, clumps are maximal overlapping sets of these occurrences. This parameter has first been studied by Schbath with the aim of counting the…

Discrete Mathematics · Computer Science 2008-04-24 Frederique Bassino , Julien Clement , Julien Fayolle , Pierre Nicodeme

A sequence $\pi_1,\pi_2,\dots$ of permutations is said to be "quasirandom" if the induced density of every permutation $\sigma$ in $\pi_n$ converges to $1/|\sigma|!$ as $n\to\infty$. We prove that $\pi_1,\pi_2,\dots$ is quasirandom if and…

Combinatorics · Mathematics 2024-10-07 Gabriel Crudele , Peter Dukes , Jonathan A. Noel