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The definition of weighted entropy allows for easy calculation of the entropy of the mixture of measures. In this paper we investigate the problem of equivalent definition of the general entropy function in weighted form. We show that under…

Information Theory · Computer Science 2013-05-15 Marek Śmieja

We study numerical integration of functions $f: \mathbb{R}^{s} \to \mathbb{R}$ with respect to a probability measure. By applying the corresponding inverse cumulative distribution function, the problem is transformed into integrating an…

Numerical Analysis · Mathematics 2025-10-01 Tiangang Cui , Josef Dick , Friedrich Pillichshammer

We present conditions that allow us to pass from the convergence of probability measures in distribution to the uniform convergence of the associated quantile functions. Under these conditions, one can in particular pass from the asymptotic…

Functional Analysis · Mathematics 2016-11-01 Johan Manuel Bogoya , Albrecht Boettcher , Egor A. Maximenko

Probabilistic submeasures generalizing the classical (numerical) submeasures are introduced and discussed in connection with some classes of aggregation functions. A special attention is paid to triangular norm-based probabilistic…

Classical Analysis and ODEs · Mathematics 2012-07-12 Lenka Halčinová , Ondrej Hutník , Radko Mesiar

Quantile and quantile effect functions are important tools for descriptive and causal analyses due to their natural and intuitive interpretation. Existing inference methods for these functions do not apply to discrete random variables. This…

Methodology · Statistics 2018-09-03 Victor Chernozhukov , Iván Fernández-Val , Blaise Melly , Kaspar Wüthrich

We present estimators for entropy and other functions of a discrete probability distribution when the data is a finite sample drawn from that probability distribution. In particular, for the case when the probability distribution is a joint…

comp-gas · Physics 2008-02-03 David H. Wolpert , David R. Wolf

We give two new simple characterizations of the Cauchy distribution by using the M\"obius and Mellin transforms. They also yield characterizations of the circular Cauchy distribution and the mixture Cauchy model.

Statistics Theory · Mathematics 2020-10-23 Kazuki Okamura

We present a theory of particles, obeying intermediate statistics ("anyons"), interpolating between Bosons and Fermions, based on the principle of Detailed Balance. It is demonstrated that the scattering probabilities of identical particles…

Quantum Physics · Physics 2008-11-26 R. Acharya , P. Narayana Swamy

We want to compute the cumulative distribution function of a one-dimensional Poisson stochastic integral $I(\krnl) = \displaystyle \int_0^T \krnl(s) N(ds)$, where $N$ is a Poisson random measure with control measure $n$ and $\krnl$ is a…

Probability · Mathematics 2010-04-30 Mark S. Veillette , Murad S. Taqqu

Quantum walks, both discrete (coined) and continuous time, form the basis of several quantum algorithms and have been used to model processes such as transport in spin chains and quantum chemistry. The enhanced spreading and mixing…

Quantum Physics · Physics 2010-12-10 Godfrey Leung , Paul Knott , Joe Bailey , Viv Kendon

We show, in a formal way, how a class of complex quasiprobability distribution functions may be introduced by using the fractional Fourier transform. This leads to the Fresnel transform of a characteristic function instead of the usual…

Quantum Physics · Physics 2019-02-19 Jorge A. Anaya-Contreras , A. Zúñiga-Segundo , Héctor M. Moya-Cessa

The distribution of the sum of independent identically distributed uniform random variables is well-known. However, it is sometimes necessary to analyze data which have been drawn from different uniform distributions. By inverting the…

Statistics Theory · Mathematics 2010-05-25 David M. Bradley , Ramesh C. Gupta

Recent literature in the last Maximum Entropy workshop introduced an analogy between cumulative probability distributions and normalized utility functions. Based on this analogy, a utility density function can de defined as the derivative…

Artificial Intelligence · Computer Science 2009-11-10 Ali E. Abbas

Numerous entropy-type characteristics (functionals) generalizing R\'enyi entropy are widely used in mathematical statistics, physics, information theory, and signal processing for characterizing uncertainty in probability distributions and…

Statistics Theory · Mathematics 2011-03-28 David Källberg , Nikolaj Leonenko , Oleg Seleznjev

We obtain exact formulas for the cumulative distribution function of the variance-gamma distribution, as infinite series involving the modified Bessel function of the second kind and the modified Lommel function of the first kind. From…

Probability · Mathematics 2024-11-20 Robert E. Gaunt

We define and study distributions in R^{d} that we call q-Normal. For q=1 they are really multidimensional Normal, for q\in(-1,1) they have densities, compact support and many properties that resemble properties of ordinary multidimensional…

Probability · Mathematics 2012-08-13 Paweł J. Szabłowski

Products between phase-type distributed random variables and any independent, positive and continuous random variable are studied. Their asymptotic properties are established, and an expectation-maximization algorithm for their effective…

Probability · Mathematics 2021-11-25 Hansjoerg Albrecher , Martin Bladt , Mogens Bladt , Jorge Yslas

Information-theoretic measures such as relative entropy and correlation are extremely useful when modeling or analyzing the interaction of probabilistic systems. We survey the quantum generalization of 5 such measures and point out some of…

Information Theory · Computer Science 2015-06-02 William Blacoe

The generalized quantal distribution functions are investigated concerning systems of non-interacting bosons and fermions. The formulae for the number of particles and energy are presented and applications to the Chandrasekhar limit of…

Statistical Mechanics · Physics 2015-06-25 Diego F. Torres , Ugur Tirnakli

In this research, Minkowski type functions which are constructed on certain probability distributions, are introduced. There are investigated differential, integral, and other properties of these functions.

Functional Analysis · Mathematics 2025-01-14 Symon Serbenyuk