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The violation of the Pauli principle has been surmised in several models of the Fractional Exclusion Statistics and successfully applied to several quantum systems. In this paper, a classical alternative of the exclusion statistics is…

Statistical Mechanics · Physics 2022-10-17 Projesh Kumar Roy

Factorized information criterion (FIC) is a recently developed approximation technique for the marginal log-likelihood, which provides an automatic model selection framework for a few latent variable models (LVMs) with tractable inference…

Machine Learning · Computer Science 2015-04-23 Kohei Hayashi , Shin-ichi Maeda , Ryohei Fujimaki

Topological objects resulting from symmetry breakdown may be either stable or metastable depending on the pattern of symmetry breaking. However, if they trap zero-energy modes of fermions, and in the process acquire non-integer fermionic…

High Energy Physics - Theory · Physics 2007-05-23 Narendra Sahu , Urjit A. Yajnik

We consider the design and analysis of multi-factor experiments using fractional factorial and incomplete designs within the potential outcome framework. These designs are particularly useful when limited resources make running a full…

Methodology · Statistics 2022-01-31 Nicole E. Pashley , Marie-Abele C. Bind

We propose a new fractional statistics for arbitrary dimensions, based on an extension of Pauli's exclusion principle, to allow for finite multi-occupancies of a single quantum state. By explicitly constructing the many-body Hilbert space,…

High Energy Physics - Theory · Physics 2010-11-01 Wei Chen , Jack Y. Ng , Hendrik van Dam

Bayesian statistical inference is a powerful tool for model-data comparisons and extractions of physical parameters that are often unknown functions of system variables. Existing Bayesian analyses often rely on explicit parametrizations of…

High Energy Physics - Phenomenology · Physics 2023-08-09 Man Xie , Weiyao Ke , Hanzhong Zhang , Xin-Nian Wang

Regression models for limited continuous dependent variables having a non-negligible probability of attaining exactly their limits are presented. The models differ in the number of parameters and in their flexibility. Fractional data being…

Applications · Statistics 2012-05-31 Fabio Sigrist , Werner A. Stahel

The estimation of the potential impact fraction (including the population attributable fraction) with continuous exposure data frequently relies on strong distributional assumptions. However, these assumptions are often violated if the…

We investigate systems of interacting stochastic differential equations with two kinds of heterogeneity: one originating from different weights of the linkages, and one concerning their asymptotic relevance when the system becomes large. To…

Probability · Mathematics 2020-06-02 Carsten Chong , Claudia Klüppelberg

We present a new method for counterfactual explanations (CFEs) based on Bayesian optimisation that applies to both classification and regression models. Our method is a globally convergent search algorithm with support for arbitrary…

Machine Learning · Computer Science 2021-06-30 Thomas Spooner , Danial Dervovic , Jason Long , Jon Shepard , Jiahao Chen , Daniele Magazzeni

The effective energy of a superconductor $E_{eff}(T)$ at temperature $T$ is defined as the difference between the total energy at temperature $T$ and the total energy at 0~K. We call the energy of the condensate, ${\mathcal E}_c$, the…

Superconductivity · Physics 2016-06-22 Dragos-Victor Anghel , George Alexandru Nemnes

Missing data are prevalent and present daunting challenges in real data analysis. While there is a growing body of literature on fairness in analysis of fully observed data, there has been little theoretical work on investigating fairness…

Machine Learning · Computer Science 2021-12-10 Yiliang Zhang , Qi Long

Counterfactual explanations (CFEs) are an emerging technique under the umbrella of interpretability of machine learning (ML) models. They provide ``what if'' feedback of the form ``if an input datapoint were $x'$ instead of $x$, then an ML…

Machine Learning · Computer Science 2021-06-16 Sahil Verma , John Dickerson , Keegan Hines

Denote by {$\times$} the fractional part. We establish several new metrical results on the distribution properties of the sequence ({x n }) n$\ge$1. Many of them are presented in a more general framework, in which the sequence of functions…

Number Theory · Mathematics 2017-10-11 Yann Bugeaud , Lingmin Liao , Michal Rams

Prior specification for nonparametric Bayesian inference involves the difficult task of quantifying prior knowledge about a parameter of high, often infinite, dimension. Realistically, a statistician is unlikely to have informed opinions…

Methodology · Statistics 2012-05-01 David C. Kessler , Peter D. Hoff , David B. Dunson

We show by microscopic calculation that thermodynamics of the multicomponent Sutherland model is equivalent to that of a free particle system with fractional exclusion statistics at all temperatures. The parameters for exclusion statistics…

Condensed Matter · Physics 2009-10-28 Yusuke Kato , Yoshio Kuramoto

A conditional version of Sibson's $\alpha$-information is defined using a simple closed-form "log-expectation" expression, which satisfies important properties such as consistency, uniform expansion, and data processing inequalities. This…

Information Theory · Computer Science 2021-05-18 Yi Liu , Wei Cheng , Sylvain Guilley , Olivier Rioul

Comment on "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]

Methodology · Statistics 2011-02-16 Hani Doss

Fractional, anomalous diffusion in space-periodic potentials is investigated. The analytical solution for the effective, fractional diffusion coefficient in an arbitrary periodic potential is obtained in closed form in terms of two…

Statistical Mechanics · Physics 2021-02-02 E. Heinsalu , M. Patriarca , I. Goychuk , P. Hanggi

We study the impacts of incomplete information on centralized one-to-one matching markets. We focus on the commonly used Deferred Acceptance mechanism (Gale and Shapley, 1962). We show that many complete-information results are fragile to a…

Theoretical Economics · Economics 2021-07-12 Marcelo Ariel Fernandez , Kirill Rudov , Leeat Yariv
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