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Deviations from scale invariance resulting from small perturbations of a general two dimensional conformal field theory are studied. They are expressed in terms of beta functions for renormalization of general couplings under local change…

High Energy Physics - Theory · Physics 2009-10-22 A. Babichenko , S. Elitzur

Statistical divergence is widely applied in multimedia processing, basically due to regularity and interpretable features displayed in data. However, in a broader range of data realm, these advantages may no longer be feasible, and…

Databases · Computer Science 2020-11-20 Ruoyu Wang , Xiaobo Hu , Daniel Sun , Guoqiang Li , Raymond Wong , Shiping Chen , Jianquan Liu

This is an expository note on useful expressions for the density function of a product of independent random variables where each variable has a Beta distribution.

Classical Analysis and ODEs · Mathematics 2013-04-25 Charles F. Dunkl

The Gaussian theory of errors has been generalized to situations, where the Gaussian distribution and, hence, the Gaussian rules of error propagation are inadequate. The generalizations are based on Bayes' theorem and a suitable measure.…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Hanns L. Harney

Generalizations of classical theta functions are proposed that include any even number of analytic parameters for which conditions of quasi-periodicity are fulfilled and that are representations of extended Heisenberg group. Differential…

Mathematical Physics · Physics 2017-07-13 Yuriy Smilyanets

We consider discrete $\beta$-ensembles, as introduced by Borodin, Gorin and Guionnet in (Publications math{\' e}matiques de l'IH{\' E}S 125, 1-78, 2017). Under general assumptions, we establish a large deviation principle for the empirical…

Probability · Mathematics 2022-05-06 Evgeni Dimitrov , Hengzhi Zhang

In general, while obtaining the probability density function of sums and products of shifted random variables, ordinary analytical methods such as Fourier and Mellin transforms tend to provide integrals which cannot be expressed in terms of…

Complex Variables · Mathematics 2013-02-14 Pushpa N. rathie , Arjun K. Rathie , Luan C. de S. M. Ozelim

In classic papers, Zellner demonstrated that Bayesian inference could be derived as the solution to an information theoretic functional. Below we derive a generalized form of this functional as a variational lower bound of a predictive…

Machine Learning · Computer Science 2019-10-25 Alexander A. Alemi

This research note deals with the evaluation of some generalized beta-type integral operators involving the multi-index Mittag-Leffler function $E_{\epsilon_{i}),(\omega_{i})}(z)$. Further, we derive a new family of beta-type integrals…

Classical Analysis and ODEs · Mathematics 2020-06-16 M. Ali , M. Ghayasuddin , R. B. Paris

This paper is devoted to the mathematical study of some divergences based on the mutual information well-suited to categorical random vectors. These divergences are generalizations of the "entropy distance" and "information distance". Their…

Statistics Theory · Mathematics 2016-08-16 Jean-François Coeurjolly , Rémy Drouilhet , Jean-François Robineau

The mean absolute deviation about the mean is an alternative to the standard deviation for measuring dispersion in a sample or in a population. For stationary, ergodic time series with a finite first moment, an asymptotic expansion for the…

Methodology · Statistics 2014-06-18 Johan Segers

We consider heteroscedastic nonparametric regression models, when both the mean function and variance function are unknown and to be estimated with nonparametric approaches. We derive convergence rates of posterior distributions for this…

Statistics Theory · Mathematics 2010-10-07 Yuao Hu

Finite sample bounds on the estimation error of the mean by the empirical mean, uniform over a class of functions, can often be conveniently obtained in terms of Rademacher or Gaussian averages of the class. If a function of n variables has…

Probability · Mathematics 2015-03-10 Andreas Maurer

Diffusion generative models unlock new possibilities for inverse problems as they allow for the incorporation of strong empirical priors in scientific inference. Recently, diffusion models are repurposed for solving inverse problems using…

Empirical Bayes methods are widely used for large-scale inference, yet most classical approaches assume homoscedastic observations and focus primarily on posterior mean estimation. We develop a nonparametric empirical Bayes framework for…

Methodology · Statistics 2026-04-24 Zhigen Zhao , Shonosuke Sugaasawa

Einstein equations for several matter sources in Robertson-Walker and Bianchi I type metrics, are shown to reduce to a kind of second order nonlinear ordinary differential equation $\ddot{y}+\alpha f(y)\dot{y}+\beta f(y)\int{f(y) dy}+\gamma…

Mathematical Physics · Physics 2009-10-30 Luis P. Chimento

This paper is concerned with the study of the consistency of a variational method for probability measure quantization, deterministically realized by means of a minimizing principle, balancing power repulsion and attraction potentials. The…

Functional Analysis · Mathematics 2013-10-07 Massimo Fornasier , Jan-Christian Hütter

The weighted forms of generalized survival and failure entropies of order ($\alpha,\beta$) are proposed and some properties are obtained. We further propose the dynamic versions of weighted generalized survival and failures entropies and…

Statistics Theory · Mathematics 2020-06-15 Siddhartha Chakraborty , Biswabrata Pradhan

For general thinning procedures, its inverse operation, the condensing, is studied and a link to integration-by-parts formulas is established. This extends the recent results on that link for independent thinnings of point processes to…

Probability · Mathematics 2017-04-26 Mathias Rafler

This PhD thesis is devoted to show that differential renormalization is a simple and useful renormalization method that we can use when dealing with gauge theories. In this work, it is shown how the one-loop results of Constraint…

High Energy Physics - Theory · Physics 2007-06-27 Cesar Seijas
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