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Measurements of a weighted energy density average taken in the vacuum state of a conformal field theory in $1+1$ dimensions are randomly distributed with vanishing expectation value. The probability distribution is computed in closed form…

High Energy Physics - Theory · Physics 2020-01-29 Matthew C. Anthony , Christopher J. Fewster

We introduce a broadly applicable statistical procedure for testing which parametric distribution family generated a random sample of data. The method, termed the Difference in Differential Entropy (DDE) test, provides a unified framework…

Econometrics · Economics 2025-12-15 Ron Mittelhammer , George Judge , Miguel Henry

We introduce a new family of one factor distributions for high-dimensional binary data. The model provides an explicit probability for each event, thus avoiding the numeric approximations often made by existing methods. Model interpretation…

Methodology · Statistics 2015-11-05 Matthieu Marbac , Mohammed Sedki

By a mixture density is meant a density of the form $\pi_{\mu}(\cdot)=\int\pi_{\theta}(\cdot)\times\mu(d\theta)$, where $(\pi_{\theta})_{\theta\in\Theta}$ is a family of probability densities and $\mu$ is a probability measure on $\Theta$.…

Statistics Theory · Mathematics 2016-08-16 François Roueff , Tobias Rydén

We present a general result giving us families of incomplete and boundedly complete families of discrete distributions. For such families, the classes of unbiased estimators of zero with finite variance and of parametric functions which…

Statistics Theory · Mathematics 2009-09-25 Sumitra Purkayastha

In this paper, we have obtained conditions on parameters that result in dispersive ordering and star ordering among two unequal sets of random variables from Proportional hazard rate and Proportional reversed hazard rate family of…

Statistics Theory · Mathematics 2020-03-02 Madhurima Datta , Nitin Gupta

Heavy-tailed random samples, as well as their sum or average, are encountered in a number of signal processing applications in radar, communications, finance, and natural sciences. Modeling such data through the Pareto distribution is…

Signal Processing · Electrical Eng. & Systems 2021-05-04 Francesco Grassi , Angelo Coluccia

Conditional independence, graphical models and sparsity are key notions for parsimonious statistical models and for understanding the structural relationships in the data. The theory of multivariate and spatial extremes describes the risk…

Statistics Theory · Mathematics 2019-11-14 Sebastian Engelke , Adrien S. Hitz

Inequality and its consequences are the subject of intense recent debate. Using a simplified model of the economy, we address the relation between inequality and liquidity, the latter understood as the frequency of economic exchanges.…

Economics · Quantitative Finance 2016-08-03 João Pedro Jerico , François P. Landes , Matteo Marsili , Isaac Pérez Castillo , Valerio Volpati

Roughness parameters that characterize contacting surfaces with regard to friction and wear are commonly stated without uncertainties, or with an uncertainty only taking into account a very limited amount of aspects such as repeatability of…

Data Analysis, Statistics and Probability · Physics 2016-07-20 Dorothee Hüser , Jonathan Hüser , Sebastian Rief , Jörg Seewig , Peter Thomsen-Schmidt

Statistical inference in parametric models (e.g., the Bradley--Terry model and its variants) for paired-comparison data has been explored in the high-dimensional regime, in which the number of items involving in paired comparisons diverges.…

Methodology · Statistics 2026-04-01 Haoyue Song , Lianqiang Qu , Ting Yan , Yuguo Chen

Herein, we review the properties of the Amoroso distribution, the natural unification of the gamma and extreme value distribution families. Over 50 distinct, named distributions (and twice as many synonyms) occur as special cases or…

Statistics Theory · Mathematics 2015-07-14 Gavin E. Crooks

Generalized linear models and the quasi-likelihood method extend the ordinary regression models to accommodate more general conditional distributions of the response. Nonparametric methods need no explicit parametric specification, and the…

Statistics Theory · Mathematics 2009-11-23 Jianqing Fan , Yichao Wu , Yang Feng

We address the problem of existence of unbiased constrained parameter estimators. We show that if the constrained set of parameters is compact and the hypothesized distributions are absolutely continuous with respect to one another, then…

Statistics Theory · Mathematics 2016-09-26 Anelia Somekh-Baruch , Amir Leshem , Venkatesh Saligrama

The "rare type match problem" is the situation in which the suspect's DNA profile, matching the DNA profile of the crime stain, is not in the database of reference. The evaluation of this match in the light of the two competing hypotheses…

Applications · Statistics 2022-05-30 Giulia Cereda , Richard D. Gill

Motivated by the need for parametric families of rich and yet tractable distributions in financial mathematics, both in pricing and risk management settings, but also considering wider statistical applications, we investigate a novel…

Statistical Finance · Quantitative Finance 2009-01-06 William T. Shaw , Ian R. C. Buckley

The unconstrained exponential family of random graphs assumes no prior knowledge of the graph before sampling, but it is natural to consider situations where partial information about the graph is known, for example the total number of…

Probability · Mathematics 2017-04-19 Richard Kenyon , Mei Yin

We introduce a simple model of economy, where the time evolution is described by an equation capturing both exchange between individuals and random speculative trading, in such a way that the fundamental symmetry of the economy under an…

Condensed Matter · Physics 2007-05-23 Jean-Philippe Bouchaud , Marc Mezard

A basic issue in both teaching of and practice of statistics is the interplay between modelling assumptions and inference performance. The general message conveyed is that stronger assumptions lead to better statistical performance of the…

Statistics Theory · Mathematics 2026-03-20 Morten Byholt , Nils Lid Hjort

We explore the interplay between random and deterministic phenomena using a representation of uncertainty based on the measure-theoretic concept of outer measure. The meaning of the analogues of different probabilistic concepts is…

Methodology · Statistics 2020-04-21 Jeremie Houssineau