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The AMAS group at the Paul Scherrer Institute developed an object oriented library for high performance simulation of high intensity ion beam transport with space charge. Such particle-in-cell (PIC) simulations require a method to generate…

Data Analysis, Statistics and Probability · Physics 2012-05-17 Christian Baumgarten

Elliptically contoured distributions can be considered to be the distributions for which the contours of the density functions are proportional ellipsoids. We generalize elliptically contoured densities to ``star-shaped distributions'' with…

Statistics Theory · Mathematics 2008-08-17 Hidehiko Kamiya , Akimichi Takemura , Satoshi Kuriki

Statistical system models provide the basis for the examination of various sorts of distributions. Classification distributions are a very common and versatile form of statistics in e.g. real economic, social, and IT systems. The…

Computation · Statistics 2019-12-20 Uwe Petersohn , Thomas Dedek , Sandra Zimmer , Hans Biskupski

This paper introduces constrained mixtures for continuous distributions, characterized by a mixture of distributions where each distribution has a shape similar to the base distribution and disjoint domains. This new concept is used to…

Machine Learning · Statistics 2015-03-29 Conrado S. Miranda , Fernando J. Von Zuben

Scattering is a ubiquitous phenomenon which is observed in a variety of physical systems which span a wide range of length scales. The scattering matrix is the key quantity which provides a complete description of the scattering process.…

Statistical Mechanics · Physics 2014-01-21 André Nock , Santosh Kumar , Hans-Jürgen Sommers , Thomas Guhr

Exact formulas are derived for the probability density functions of the sum and difference of two independent non-central gamma distributed random variables, with both series and integral representations of the density presented. These…

Probability · Mathematics 2026-05-18 Robert E. Gaunt , Heather L. Sutcliffe

This paper presents a procedure for testing the hypothesis that the underlying distribution of the data is elliptical when using robust location and scatter estimators instead of the sample mean and covariance matrix. Under mild assumptions…

Methodology · Statistics 2015-02-20 Ana M. Bianco , Graciela Boente , Isabel M. Rodrigues

This paper proposes famillies of multimatricvariate and multimatrix variate distributions based on elliptically contoured laws in the context of real normed division algebras. The work allows to answer the following inference problems about…

Statistics Theory · Mathematics 2024-05-14 José A. Díaz-García , Francisco J. Caro-Lopera

We develop a class of non-Gaussian translation processes that extend classical stochastic differential equations (SDEs) by prescribing arbitrary absolutely continuous marginal distributions. Our approach uses a copula-based transformation…

Statistics Theory · Mathematics 2025-08-06 Robert Richardson , H. Dennis Tolley , Kenneth Kuttler

We introduce a novel family of projected distributions on the circle and the sphere, namely the circular and spherical projected Cauchy distributions, as promising alternatives for modelling circular and spherical data. The circular…

Methodology · Statistics 2024-09-12 Michail Tsagris , Omar Alzeley

The envelope of an elliptical Gaussian complex vector, or equivalently, the amplitude or norm of a bivariate normal random vector has application in many weather and signal processing contexts. We explicitly characterize its distribution in…

Statistics Theory · Mathematics 2026-02-03 Sattwik Ghosal , Ranjan Maitra

This paper deals with the Elliptical Wishart and Inverse Elliptical Wishart distributions, which play a major role when handling covariance matrices. Similarly to multivariate elliptical distributions, these form a large family of…

Statistics Theory · Mathematics 2024-11-01 Imen Ayadi , Florent Bouchard , Frédéric Pascal

A new family of distributions indexed by the class of matrix variate contoured elliptically distribution is proposed as an extension of some bimatrix variate distributions. The termed \emph{multimatrix variate distributions} open new…

Statistics Theory · Mathematics 2024-05-07 José A. Díaz-García , Francisco J. Caro-Lopera

A large class of modern probabilistic learning systems assumes symmetric distributions, however, real-world data tend to obey skewed distributions and are thus not always adequately modelled through symmetric distributions. To address this…

Machine Learning · Statistics 2021-03-16 Shengxi Li , Danilo Mandic

This paper extends the notion of the matrix angular central distribution (MACG) to the complex case. We start by considering the normally distributed random complex matrix ($Z$) and show that is the orientation ($H_Z=Z(Z'Z)^{-1}$) has…

Statistics Theory · Mathematics 2020-10-08 Justyna Wróblewska

This article derives several properties of the Riesz distributions, such as their corresponding Bartlett decompositions, the inverse Riesz distributions and the distribution of the generalised variance for real normed division algebras. In…

Statistics Theory · Mathematics 2015-06-17 José A. Diaz-Garcia

In the $(\lambda_{\rm R}, \varepsilon)$ and $(V/\sigma, \varepsilon)$ diagrams for characterizing dynamical states, the fast-rotator galaxies (both early-type and spirals) are distributed within a well-defined leaf-shaped envelope. This was…

Astrophysics of Galaxies · Physics 2020-11-04 Bitao Wang , Michele Cappellari , Yingjie Peng

Elliptically symmetric distributions are widely used in portfolio modeling, as well as in signal processing applications for modeling impulsive background noises. Of particular interest are algorithms for covariance estimation and subspace…

Statistics Theory · Mathematics 2016-12-01 Christophe Culan , Claude Adnet

A definition for elliptical tempered stable distribution, based on the characteristic function, have been explained which involve a unique spectral measure. This definition provides a framework for creating a connection between infinite…

Probability · Mathematics 2014-08-18 Hassan A. Fallahgoul , Young S. Kim

Robustly determining the optimal number of clusters in a data set is an essential factor in a wide range of applications. Cluster enumeration becomes challenging when the true underlying structure in the observed data is corrupted by…

Signal Processing · Electrical Eng. & Systems 2021-05-06 Christian A. Schroth , Michael Muma