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Probabilities of causation (PoCs), such as the probability of necessity and sufficiency (PNS), are important tools for decision making but are generally not point identifiable. Existing work has derived bounds for these quantities using…

Methodology · Statistics 2026-02-20 Tianyuan Cheng , Ruirui Mao , Judea Pearl , Ang Li

The distance and divergence of the probability measures play a central role in statistics, machine learning, and many other related fields. The Wasserstein distance has received much attention in recent years because of its distinctions…

Statistics Theory · Mathematics 2021-03-11 Qijun Tong , Kei Kobayashi

A theory of quantitative inference about the parameters of sampling distributions is constructed deductively by following very general rules, referred to as the Cox-Polya-Jaynes Desiderata. The inferences are made in terms of probability…

Statistics Theory · Mathematics 2017-08-23 Tomaz Podobnik , Tomi Zivko

A new method of deriving comparative statics information using generalized compensated derivatives is presented which yields constraint-free semidefiniteness results for any differentiable, constrained optimization problem. More generally,…

Optimization and Control · Mathematics 2013-10-29 M. Hossein Partovi , Michael R. Caputo

The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce. In particular, knowing the joint distribution of the pair Entropy-Statistical Complexity for a large class…

Reconciliation enforces coherence between hierarchical forecasts, in order to satisfy a set of linear constraints. While most works focus on the reconciliation of the point forecasts, we consider probabilistic reconciliation and we analyze…

Applications · Statistics 2024-02-15 Lorenzo Zambon , Arianna Agosto , Paolo Giudici , Giorgio Corani

It is well understood that Bayesian decision theory and average case analysis are essentially identical. However, if one is interested in performing uncertainty quantification for a numerical task, it can be argued that standard approaches…

Methodology · Statistics 2020-07-16 Chris. J. Oates , Jon Cockayne , Dennis Prangle , T. J. Sullivan , Mark Girolami

We show that starting with either the non-extensive Tsallis entropy in Wang's formalism or the extensive Renyi entropy, it is possible to construct the equilibrium statistical mechanics with non-Gibbs canonical distribution functions. The…

High Energy Physics - Phenomenology · Physics 2009-11-10 A. S. Parvan , T. S. Biro

We derive some Quantum Central Limit Theorems for expectation values of macroscopically coarse-grained observables, which are functions of coarse-grained hermitean operators. Thanks to the hermicity constraints, we obtain positive-definite…

Quantum Physics · Physics 2023-12-06 Tien D. Kieu

The conventional approach to fixed-order perturbative QCD predictions is based on an arbitrary choice of the renormalization scale, together with an arbitrary range. This {\it ad hoc} assignment of the renormalization scale causes the…

High Energy Physics - Phenomenology · Physics 2019-12-19 Xing-Gang Wu , Jian-Ming Shen , Bo-Lun Du , Xu-Dong Huang , Sheng-Quan Wang , Stanley J. Brodsky

This paper modifies Jaynes's axioms of plausible reasoning and derives the minimum relative entropy principle, Bayes's rule, as well as maximum likelihood from first principles. The new axioms, which I call the Optimum Information…

Information Theory · Computer Science 2011-03-30 Alexis Akira Toda

A thermodynamic-like formalism is developed for superstatistical systems based on conditional entropies. This theory takes into account large-scale variations of intensive variables of systems in nonequilibrium stationary states. Ordinary…

Statistical Mechanics · Physics 2009-11-13 Sumiyoshi Abe , Christian Beck , E. G. D. Cohen

We show that the Jaynes principle is indeed a proper inference scheme when applied to compound systems and will correctly produce the entangled maximum entropy states compatible with appropriate data. This is accomplished by including the…

Quantum Physics · Physics 2008-12-18 A. K. Rajagopal

We study an entropy measure for quantum systems that generalizes the von Neumann entropy as well as its classical counterpart, the Gibbs or Shannon entropy. The entropy measure is based on hypothesis testing and has an elegant formulation…

Quantum Physics · Physics 2014-02-19 F. Dupuis , L. Kraemer , P. Faist , J. M. Renes , R. Renner

Alternative definitions are given of basic concepts of generalized thermostatistics. In particular, generalizations of Shannon's entropy, of the Boltzmann-Gibbs distribution, and of relative entropy are considered. Particular choices made…

Statistical Mechanics · Physics 2007-05-23 Jan Naudts

The theory of large deviations deals with the probabilities of rare events (or fluctuations) that are exponentially small as a function of some parameter, e.g., the number of random components of a system, the time over which a stochastic…

Statistical Mechanics · Physics 2012-03-01 Hugo Touchette

We discuss two families of two-parameter entropies and divergences, derived from the standard R\'enyi and Tsallis entropies and divergences. These divergences and entropies are found as divergences or entropies of escort distributions.…

Mathematical Physics · Physics 2011-09-16 J. -F. Bercher

The incomplete nonextensive statistics in the canonical and microcanonical ensembles is explored in the general case and in a particular case for the ideal gas. By exact analytical results for the ideal gas it is shown that taking the…

Statistical Mechanics · Physics 2011-01-17 A. S. Parvan , T. S. Biro

Tsallis' non-extensive entropy $S_q$ enables us to treat both a power and exponential evolutions of underlying microscopic dynamics on equal footing by adjusting the variable entropic index $q$ to proper one $q^*$. We propose an alternative…

Statistical Mechanics · Physics 2009-11-07 Wada Tatsuaki , Saito Takeshi

The theory of large deviations constitutes a mathematical cornerstone in the foundations of Boltzmann-Gibbs statistical mechanics, based on the additive entropy $S_{BG}=- k_B\sum_{i=1}^W p_i \ln p_i$. Its optimization under appropriate…

Statistical Mechanics · Physics 2011-10-31 Guiomar Ruiz , Constantino Tsallis
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