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We introduce the beta generalized exponential distribution that includes the beta exponential and generalized exponential distributions as special cases. We provide a comprehensive mathematical treatment of this distribution. We derive the…

Methodology · Statistics 2010-08-17 Wagner Barreto-Souza , Alessandro H. S. Santos , Gauss M. Cordeiro

For a sample of absolutely bounded i.i.d. random variables with a continuous density the cumulative distribution function of the sample variance is represented by a univariate integral over a Fourier series. If the density is a polynomial…

Statistics Theory · Mathematics 2008-10-10 T. Royen

We show a general relation between the spatially disjoint product of probability density functions and the sum of their Fisher information metric tensors. We then utilise this result to give a method for constructing the probability density…

Information Theory · Computer Science 2015-04-14 T. Clingman , Jeff Murugan , Jonathan P. Shock

We find a formula that relates the Fourier transform of a radial function on $\mathbf{R}^n$ with the Fourier transform of the same function defined on $\mathbf{R}^{n+2}$. This formula enables one to explicitly calculate the Fourier…

Classical Analysis and ODEs · Mathematics 2013-02-19 Loukas Grafakos , Gerald Teschl

The Wishart distribution and its generalizations are among the most prominent probability distributions in multivariate statistical analysis, arising naturally in applied research and as a basis for theoretical models. In this paper, we…

Statistics Theory · Mathematics 2015-02-26 A. Bekker , M. Arashi , J. van Niekerk

The generalized partially linear models on Riemannian manifolds are introduced. These models, like ordinary generalized linear models, are a generalization of partially linear models on Riemannian manifolds that allow for response variables…

Methodology · Statistics 2018-03-09 Amelia Simó , M. Victoria Ibáñez , Irene Epifanio , Vicent Gimeno

Mutual space-frequency distribution is proposed and it is shown that Wigner and Weyl distribution functions are only particular cases of these distribution. Mutual distribution for Gaussian signal is analytically obtained. The simple…

Popular Physics · Physics 2008-10-16 Yura Kozlovskii

In this paper, we obtain various series and asymptotic expansions involving the modified Bessel function of the second kind for the normal inverse Gaussian cumulative distribution function. The new expansions accelerate computations,…

Numerical Analysis · Mathematics 2025-02-25 Guillermo Navas-Palencia

We prove several new results on the Hamming weight of bounded uniform and small-bias distributions. We exhibit bounded-uniform distributions whose weight is anti-concentrated, matching existing concentration inequalities. This construction…

Computational Complexity · Computer Science 2024-07-18 Harm Derksen , Peter Ivanov , Chin Ho Lee , Emanuele Viola

We introduce a variant of the replica trick within the nonlinear sigma model that allows calculating the distribution function of the persistent current. In the diffusive regime, a Gaussian distribution is derived. This result holds in the…

Mesoscale and Nanoscale Physics · Physics 2010-11-02 M. Houzet

We investigate the distribution of the zeros of partial sums of the Riemann zeta-function, sum_{n\leq X}n^{-s}, estimating the number of zeros up to height T, the number of zeros to the right of a given vertical line, and other aspects of…

Number Theory · Mathematics 2008-07-02 S. M. Gonek , A. H. Ledoan

Calculation of the distribution of the average value of a Gaussian random field in a finite domain is carried out for different cases. The results of the calculation demonstrate a strong dependence of the width of the distribution on the…

Disordered Systems and Neural Networks · Physics 2015-05-13 S. V. Novikov , M. Van der Auweraer

We have investigated a weighted chi-square distribution of the variable $\xi$ which is a weighted sum of squared normally distributed independent variables whose weights are cosines of angles $\phi_k=2\pi k/N$, where $k \in \{0,1,...,N-1\}$…

Disordered Systems and Neural Networks · Physics 2024-12-24 Vladislav Egorov , Boris Kryzhanovsky

Matrix multivariate Pearson type II-Riesz distribution is defined and some of its properties are studied. In particular, the associated matrix multivariate beta distribution type I is derived. Also the singular values and eigenvalues…

Statistics Theory · Mathematics 2015-06-25 Jose A. Diaz-Garcia , Ramon Gutierrez-Sanchez

We study a discrete analogue of the classical multivariate Gaussian distribution. It is supported on the integer lattice and is parametrized by the Riemann theta function. Over the reals, the discrete Gaussian is characterized by the…

Algebraic Geometry · Mathematics 2019-04-19 Daniele Agostini , Carlos Améndola

We construct a generalization of the multiplicative product of distributions presented by L. H\"ormander in [L. H\"ormander, {\it The analysis of linear partial differential operators I} (Springer-Verlag, 1983)]. The new product is defined…

Functional Analysis · Mathematics 2009-07-14 Nuno Costa Dias , Joao Nuno Prata

Assuming the Riemann hypothesis, we investigate the distribution of gaps between the zeros of \xi'(s). We prove that a positive proportion of gaps are less than 0.796 times the average spacing and, in the other direction, a positive…

Number Theory · Mathematics 2012-11-06 H. M. Bui

A generalization of a distribution increases the flexibility particularly in studying of a phenomenon and its properties. Many generalizations of continuous univariate distributions are available in literature. In this study, an…

Applications · Statistics 2024-08-30 Brijesh P. Singh , Sandeep Singh , Utpal Dhar Das

The Poisson-binomial distribution is useful in many applied problems in engineering, actuarial science, and data mining. The Poisson-binomial distribution models the distribution of the sum of independent but not identically distributed…

Computation · Statistics 2017-02-07 Man Zhang , Yili Hong , Narayanaswamy Balakrishnan

We present a new approximation to the normal distribution quantile function. It has a similar form to the approximation of Beasley and Springer [3], providing a maximum absolute error of less than $2.5 \cdot 10^{-5}$. This is less accurate…

Computation · Statistics 2010-02-03 Paul M. Voutier