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Large deviation principles and related results are given for a class of Markov chains associated to the "leaves" in random recursive trees and preferential attachment random graphs, as well as the "cherries" in Yule trees. In particular,…

Probability · Mathematics 2010-01-22 W. Bryc , D. Minda , S. Sethuraman

Contents: A. Introduction B. High Temperature Expansions for the Ising Model C. Characteristic Functions and Cumulants D. The One Dimensional Chain E. Directed Paths and the Transfer Matrix F. Moments of the Correlation Function G. The…

Condensed Matter · Physics 2007-05-23 Mehran Kardar

The likelihood function is central to both frequentist and Bayesian formulations of parametric statistical inference, and large-sample approximations to the sampling distributions of estimators and test statistics, and to posterior…

Methodology · Statistics 2022-04-05 Anthony C. Davison , Nancy Reid

Randomness is viewed through an analogy between a physical quantity, density of gas, and a mathematical construct -- probability density. Boltzmann's deduction of equilibrium distribution of ideal gas placed in an external potential field…

Probability · Mathematics 2012-08-27 M. Grendar, , M. Grendar

It is shown that under standard hypotheses, if stochastic approximation iterates remain tight, they converge with probability one to what their o.d.e. limit suggests. A simple test for tightness (and therefore a.s. convergence) is provided.…

Probability · Mathematics 2010-07-28 Sameer Kamal

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

Understanding rare events is critical across domains ranging from signal processing to reliability and structural safety, extreme-weather forecasting, and insurance. The analysis of rare events is a computationally challenging problem,…

Probability · Mathematics 2025-11-18 Anya Katsevich , Alexander Katsevich

Let $X$ be a discrete random variable with support $S$ and $f : S \to S^\prime$ be a bijection. Then it is well-known that the entropy of $X$ is the same as the entropy of $f(X)$. This entropy preservation property has been well-utilized to…

Information Theory · Computer Science 2007-07-13 Chandra Nair , Balaji Prabhakar , Devavrat Shah

We study the entropy $S$ of longest increasing subsequences (LIS), i.e., the logarithm of the number of distinct LIS. We consider two ensembles of sequences, namely random permutations of integers and sequences drawn i.i.d.\ from a limited…

Disordered Systems and Neural Networks · Physics 2020-06-09 Phil Krabbe , Hendrik Schawe , Alexander K. Hartmann

This note continues investigation of randomness-type properties emerging in idealized financial markets with continuous price processes. It is shown, without making any probabilistic assumptions, that the strong variation exponent of…

Trading and Market Microstructure · Quantitative Finance 2010-11-25 Vladimir Vovk

If the inflaton sector is described by softly broken supersymmetry, and the inflaton has unsuppressed couplings, the inflaton mass will run strongly with scale. Four types of model are possible. The prediction for the spectral index…

High Energy Physics - Phenomenology · Physics 2009-10-31 Laura Covi , David H. Lyth

Hybrid continuous-discrete models naturally represent many real-world applications in robotics, finance, and environmental engineering. Inference with large-scale models is challenging because relational structures deteriorate rapidly…

Machine Learning · Computer Science 2012-10-19 Jaesik Choi , Eyal Amir

Let $R$ be a finite ring. The commuting probability of $R$ is the probability that any two randomly chosen elements of $R$ commute. In this paper, we obtain some bounds for commuting probability of $R$.

Rings and Algebras · Mathematics 2017-02-08 Jutirekha Dutta , Dhiren Kumar Basnet

A discrete-time totally asymmetric simple exclusion process on a lattice with open boundaries is considered. There are particles of different types. The type of a particle is characterized by the probability that a particle moves to a…

Statistical Mechanics · Physics 2025-11-04 Marina V. Yashina , Alexander G. Tatashev

An analytical expression of probability density function (PDF) of accelerations in turbulence is derived with the help of the multifractal analysis based on generalized entropy, i.e., the Tsallis or the R\'{e}nyi entropy. It is shown that…

Statistical Mechanics · Physics 2007-05-23 Toshihico Arimitsu , Naoko Arimitsu

This text presents an unified approach of probability and statistics in the pursuit of understanding and computation of randomness in engineering or physical or social system with prediction with generalizability. Starting from elementary…

History and Overview · Mathematics 2024-01-19 Lakshman Mahto

We report experimental results on the acceleration component probability distribution function at $R_\lambda = 690$ to probabilities of less than $10^{-7}$. This is an improvement of more than an order of magnitude over past measurements…

Fluid Dynamics · Physics 2007-05-23 Nicolas Mordant , Alice M. Crawford , Eberhard Bodenschatz

We present a theory to obtain the pressure tensor for a class of non-ideal multicomponent lattice Boltzmann models, thus extending the theory presented by Shan (X. Shan, Phys. Rev. E 77, 066702 (2008)) for single component fluids. We obtain…

Statistical Mechanics · Physics 2014-02-20 M. Sbragaglia , D. Belardinelli

In this study, the cumulative effect of the empirical probability distribution of a random variable is identified as a factor that amplifies the occurrence of extreme events in datasets. To quantify this observation, a corresponding…

We present an extension of the framework introduced in [1] to treat multicomponent systems, showing that new degrees of freedom are necessary in order to obtain the desired boundary conditions. We then apply this extended framework to the…

Quantum Gases · Physics 2019-02-01 Luca Mingarelli , Eric E Keaveny , Ryan Barnett