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$f$-divergences are a general class of divergences between probability measures which include as special cases many commonly used divergences in probability, mathematical statistics and information theory such as Kullback-Leibler…

Statistics Theory · Mathematics 2013-10-16 Adityanand Guntuboyina , Sujayam Saha , Geoffrey Schiebinger

We obtain bounds to quantify the distributional approximation in the delta method for vector statistics (the sample mean of $n$ independent random vectors) for normal and non-normal limits, measured using smooth test functions. For normal…

Statistics Theory · Mathematics 2023-05-11 Robert E. Gaunt , Heather Sutcliffe

Computable solutions for expectations of Continuous Ranked Probability Scores are presented. After deriving a scale invariant version of these scores, a closed form for the convolutions of scores is presented. This closed form enables the…

Methodology · Statistics 2023-04-20 Tina Nane , Roger Cooke

This work presents a novel approach to the mean-square analysis of the normalized least mean squares (NLMS) algorithm for circular complex colored Gaussian inputs. The analysis is based on the derivation of a closed-form expression for the…

Signal Processing · Electrical Eng. & Systems 2021-08-10 Tareq Y. Al-Naffouri , Muhammad Moinuddin , Anum Ali

In this paper we demonstrate that multi-modal Probability Distribution Functions (PDFs) may be efficiently sampled using an algorithm originally developed for numerical integrations by Monte-Carlo methods. This algorithm can be used to…

Computational Physics · Physics 2009-10-31 K. J. Abraham , L. M. Haines

The generalized inverse Gaussian, denoted $\mathrm{GIG}(p, a, b)$, is a flexible family of distributions that includes the gamma, inverse gamma, and inverse Gaussian distributions as special cases. In addition to its applications in…

Computation · Statistics 2025-01-28 Victor Peña , Michael Jauch

The aim of this paper is to propose diffusion strategies for distributed estimation over adaptive networks, assuming the presence of spatially correlated measurements distributed according to a Gaussian Markov random field (GMRF) model. The…

Systems and Control · Computer Science 2015-06-22 Paolo Di Lorenzo

This paper shows that the weighting coefficient matrices of the differential quadrature method (DQM) are centrosymmetric or skew-centrosymmetric if the grid spacings are symmetric irrespective of whether they are equal or unequal. A new…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 W Chen , Xinwei Wang , Yongxi Yu

A probabilistic circuit (PC) succinctly expresses a function that represents a multivariate probability distribution and, given sufficient structural properties of the circuit, supports efficient probabilistic inference. Typically a PC…

Machine Learning · Computer Science 2024-08-09 Oliver Broadrick , William Cao , Benjie Wang , Martin Trapp , Guy Van den Broeck

Applying the standard weighted mean formula, [sum_i {n_i sigma^{-2}_i}] / [sum_i {sigma^{-2}_i}], to determine the weighted mean of data, n_i, drawn from a Poisson distribution, will, on average, underestimate the true mean by ~1 for all…

Astrophysics · Physics 2009-10-31 Kenneth J. Mighell

In this paper, we state and prove a simple geometric interpretation of the degrees of freedom of a chi-square distribution. The general geometric idea goes back at least to Fisher in the 1920s, but the exact result does not appear to have…

Other Statistics · Statistics 2023-05-18 James Bernhard

We represent the product of two correlated normal random variables, and more generally the sum of independent copies of such random variables, as a difference of two independent noncentral chi-square random variables (which we refer to as…

Probability · Mathematics 2025-09-05 Robert E. Gaunt

Translational diffusion coefficients are routinely estimated from molecular dynamics simulations. Linear fits to mean squared displacement (MSD) curves have become the de facto standard, from simple liquids to complex biomacromolecules.…

Computational Physics · Physics 2020-11-20 Jakob Tómas Bullerjahn , Sören von Bülow , Gerhard Hummer

In this paper, an alternative Discrete skew Logistic distribution is proposed, which is derived by using the general approach of discretizing a continuous distribution while retaining its survival function. The properties of the…

Methodology · Statistics 2016-04-07 Deepesh Bhati , Subrata Chakraborty , Snober Gowhar Lateef

Wave-CAIPI MR imaging is a 3D imaging technique which can uniformize the g-factor maps and significantly reduce g-factor penalty at high acceleration factors. But it is time-consuming to calculate the average g-factor penalty for optimizing…

Medical Physics · Physics 2019-03-18 Haifeng Wang , Zhilang Qiu , Shi Su , Leslie Ying , Dong Liang

We give a number of theoretical and practical methods related to the computation of L-functions, both in the local case (counting points on varieties over finite fields, involving in particular a detailed study of Gauss and Jacobi sums),…

Number Theory · Mathematics 2018-10-01 Henri Cohen

A new method that enables easy and convenient discretization of partial differential equations with derivatives of arbitrary real order (so-called fractional derivatives) and delays is presented and illustrated on numerical solution of…

Numerical Analysis · Mathematics 2009-03-06 Igor Podlubny , Aleksei V. Chechkin , Tomas Skovranek , YangQuan Chen , Blas M. Vinagre Jara

Some new survival distributions are introduced based on a generalised exponential function. This class of distributions includes heavy-tailed generalisations of exponential, Weibull and gamma distributions. Properties of the distributions…

Methodology · Statistics 2014-12-03 Rose Baker

Anomalous diffusion is a phenomenon that cannot be modeled accurately by second-order diffusion equations, but is better described by fractional diffusion models. The nonlocal nature of the fractional diffusion operators makes substantially…

Numerical Analysis · Mathematics 2018-03-08 K. Mustapha , K. Furati , O. M. Knio , O. Le Maitre

A framework for robust optimization under uncertainty based on the use of the generalized inverse distribution function (GIDF), also called quantile function, is here proposed. Compared to more classical approaches that rely on the usage of…

Optimization and Control · Mathematics 2014-07-18 Domenico Quagliarella , Giovanni Petrone , Gianluca Iaccarino
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