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This paper presents an approach for developing the explanation capabilities of rule-based expert systems managing imprecise and uncertain knowledge. The treatment of uncertainty takes place in the framework of possibility theory where the…

Artificial Intelligence · Computer Science 2013-04-08 Henri Farrency , Henri Prade

Arising out of an attempt at a new foundations of mathematics, in which relations are more primitive than sets, and out of the theoretical physicists' concept of underlying causes of empirical phenomena, the idea of a purely mathematical…

History and Philosophy of Physics · Physics 2011-11-22 Helier Robinson

Estimating the number of unseen species is an important problem in many scientific endeavors. Its most popular formulation, introduced by Fisher, uses $n$ samples to predict the number $U$ of hitherto unseen species that would be observed…

Statistics Theory · Mathematics 2016-03-04 Alon Orlitsky , Ananda Theertha Suresh , Yihong Wu

With contemporary data sets becoming too large to analyze the data directly, various forms of aggregated data are becoming common. The original individual data are points, but after aggregation, the observations are interval-valued (e.g.).…

Methodology · Statistics 2023-09-21 S. Yaser Samadi , L. Billard , Jiin-Huarng Guo , Wei Xu

Since its introduction by Fisher, the method of hypothesis testing that relies on computing error probabilities has witnessed several developments. Perhaps the most significant development was the seminal contributions of Neyman and Pearson…

Other Statistics · Statistics 2026-05-08 Reason Machete

The minimax risk is often considered as a gold standard against which we can compare specific statistical procedures. Nevertheless, as has been observed recently in robust and heavy-tailed estimation problems, the inherent reduction of the…

Statistics Theory · Mathematics 2024-07-08 Tianyi Ma , Kabir A. Verchand , Richard J. Samworth

We prove necessary optimality conditions of Euler-Lagrange type for generalized problems of the calculus of variations on time scales with a Lagrangian depending not only on the independent variable, an unknown function and its delta…

Optimization and Control · Mathematics 2011-05-02 Natalia Martins , Delfim F. M. Torres

This is an invited contribution to the discussion on Professor Deborah Mayo's paper, "On the Birnbaum argument for the strong likelihood principle," to appear in Statistical Science. Mayo clearly demonstrates that statistical methods…

Statistics Theory · Mathematics 2014-11-05 Ryan Martin , Chuanhai Liu

The use of {\it Mathematica} in deriving mean likelihood estimators is discussed. Comparisons between the maximum likelihood estimator, the mean likelihood estimator and the Bayes estimate based on a Jeffrey's noninformative prior using the…

Statistics Theory · Mathematics 2016-11-04 Ian McLeod , Benoit Quenneville

It is part of our daily social-media experience that seemingly ordinary items (videos, news, publications, etc.) unexpectedly gain an enormous amount of attention. Here we investigate how unexpected these events are. We propose a method…

Physics and Society · Physics 2014-12-09 José M. Miotto , Eduardo G. Altmann

The mark-recapture method was devised by Petersen in 1896 to estimate the number of fish migrating into the Limfjord, and independently by Lincoln in 1930 to estimate waterfowl abundance. The technique applies to any search for a finite…

Statistics Theory · Mathematics 2013-06-03 Anthony J Webster , Richard Kemp

Classical inequalities used in information theory such as those of de Bruijn, Fisher, and Kullback carry over from the setting of probability theory on Euclidean space to that of unimodular Lie groups. These are groups that posses…

Information Theory · Computer Science 2009-06-02 Gregory S. Chirikjian

In biology, information flows from the environment to the genome by the process of natural selection. But it has not been clear precisely what sort of information metric properly describes natural selection. Here, I show that Fisher…

Populations and Evolution · Quantitative Biology 2009-06-18 Steven A. Frank

We propose a new family of fairness definitions for classification problems that combine some of the best properties of both statistical and individual notions of fairness. We posit not only a distribution over individuals, but also a…

Machine Learning · Computer Science 2019-12-18 Michael Kearns , Aaron Roth , Saeed Sharifi-Malvajerdi

There is a large body of evidence that decision makers frequently depart from Bayesian updating. This paper introduces a model, robust maximum likelihood (RML) updating, where deviations from Bayesian updating are due to multiple…

Theoretical Economics · Economics 2025-12-17 Elchin Suleymanov

Exponential families form the backbone of modern statistics and machine learning, but textbooks seldom derive them from first principles in an accessible way. Although minimal sufficiency and the principle of maximum entropy, originating in…

Methodology · Statistics 2026-04-27 Korbinian Strimmer

If wealthier people have advantages in having higher returns than poor, inequality will unequivocally increase, but is equal opportunity enough to prevent it? According to several models in economics and econophysics, no. They all display…

Statistical Mechanics · Physics 2022-01-21 Ben-Hur Francisco Cardoso , Sebastián Gonçalves , José Roberto Iglesias

If the quantum mechanical description of reality is not complete and a hidden variable theory is possible, what arises is the problem to explain where the rates of the outcomes of statistical experiments come from, as already noticed by…

Quantum Physics · Physics 2007-05-23 Bruno Galvan

The paper aims at reconsidering the famous Le Cam LAN theory. The main features of the approach which make it different from the classical one are as follows: (1) the study is nonasymptotic, that is, the sample size is fixed and does not…

Statistics Theory · Mathematics 2013-03-06 Vladimir Spokoiny

The designation ``Bernstein-von Mises theorem'' is apparently due to Lucien Le Cam. Roughly, the assertion of this theorem states that the posterior distribution of a parameter, conditioned on a large sample, is approximately normal,…

Statistics Theory · Mathematics 2025-12-16 Hans Fischer