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We introduce the free analogue of the classical beta prime distribution by the multiplicative free convolution of the free Poisson and the reciprocal of free Poisson distributions, and related free analogues of the classical $F$, $T$, and…

Probability · Mathematics 2019-06-04 Hiroaki Yoshida

The Transformed-Transformer family of distributions are the resulting family of distributions as transformed from a random variable $T$ through another transformer random variable $X$ using a weight function $\omega$ of the cumulative…

Methodology · Statistics 2016-02-18 Nil Kamal Hazra , Pradip Kundu , Asok K. Nanda

This paper explores mixture distributions induced by a product of the positive stable random variable and a power of another positive random variable. The paper also considers the convolution of the stable density with a gamma density.…

Probability · Mathematics 2025-07-10 Nomvelo Karabo Sibisi

In our previous work we found sufficient conditions to be imposed on the parameters of the generalized hypergeometric function in order that it be completely monotonic or of Stieltjes class. In this paper we collect a number of consequences…

Classical Analysis and ODEs · Mathematics 2017-06-23 D. B. Karp , E. G. Prilepkina

We are studying here a family of probability density functions indexed by a real parameter, and constructed from homographic relations between associated Stieltjes transforms. From the analysis of orthogonal polynomials we deduce a family…

Classical Analysis and ODEs · Mathematics 2011-05-12 Roland Groux

In this paper, we derive the analytical behavior of the limiting spectral distribution of non-central covariance matrices of the "general information-plus-noise" type, as studied in [14]. Through the equation defining its Stieltjes…

Statistics Theory · Mathematics 2023-06-29 Huanchao Zhou , Jiang Hu , Zhidong Bai , Jack W. Silverstein

This paper is a study of power series, where the coefficients are binomial expressions (iterated finite differences). Our results can be used for series summation, for series transformation, or for asymptotic expansions involving Stirling…

Number Theory · Mathematics 2016-10-10 Khristo N. Boyadzhiev

In recent years, a rich variety of shrinkage priors have been proposed that have great promise in addressing massive regression problems. In general, these new priors can be expressed as scale mixtures of normals, but have more complex…

Methodology · Statistics 2012-03-15 Artin Armagan , David B. Dunson , Merlise Clyde

Suppose that P_{\theta}(g) is a linear functional of a Dirichlet process with shape \theta H, where \theta >0 is the total mass and H is a fixed probability measure. This paper describes how one can use the well-known Bayesian prior to…

Statistics Theory · Mathematics 2007-06-13 Lancelot F. James

Probability distributions supported on the simplex enjoy a wide range of applications across statistics and machine learning. Recently, a novel family of such distributions has been discovered: the continuous categorical. This family enjoys…

In this paper we introduce a new flexible class of distributions with bounded support, called reflected Generalized Topp-Leone Power Series (rGTL-PS), obtained by compounding the reflected Generalized Topp-Leone (van Drop and Kotz, 2006)…

Methodology · Statistics 2016-07-20 Francesca Condino , Filippo Domma

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

Gaussian distributions can be generalized from Euclidean space to a wide class of Riemannian manifolds. Gaussian distributions on manifolds are harder to make use of in applications since the normalisation factors, which we will refer to as…

Probability · Mathematics 2023-02-16 Simon Heuveline , Salem Said , Cyrus Mostajeran

Classical random matrix ensembles with orthogonal symmetry have the property that the joint distribution of every second eigenvalue is equal to that of a classical random matrix ensemble with symplectic symmetry. These results are shown to…

Mathematical Physics · Physics 2015-06-24 Peter J. Forrester

In this paper new series for the first and second Stieltjes constants (also known as generalized Euler's constant), as well as for some closely related constants are obtained. These series contain rational terms only and involve the…

Number Theory · Mathematics 2017-04-18 Iaroslav V. Blagouchine , Marc-Antoine Coppo

The break-by-one gamma distribution has a probability density function resembling the Schechter function, but with the small-argument behavior modified so it is normalizable in commonly arising cases where the Schechter function is not. Its…

Cosmology and Nongalactic Astrophysics · Physics 2020-07-31 Thomas J. Loredo

The distributions of the number of occurrences of words (the distributions of words for short) play key roles in information theory, statistics, probability theory, ergodic theory, computer science, and DNA analysis. Bassino et al. 2010 and…

Information Theory · Computer Science 2022-11-16 Hayato Takahashi

We study the evolution of zeros of high polynomial powers under the heat flow. For any fixed polynomial $P(z)$, we prove that the empirical zero distribution of its heat-evolved $n$-th power converges to a distribution on the complex plane…

Probability · Mathematics 2025-12-22 Antonia Höfert , Jonas Jalowy , Zakhar Kabluchko

Let d\mu(t) be a probability measure on [0,+\infty) such that its moments are finite. Then the Cauchy-Stieltjes transform S of d\mu(t) is a Stieltjes function, which admits an expansion into a Stieltjes continued fraction. In the present…

Classical Analysis and ODEs · Mathematics 2012-12-06 Maxim Derevyagin

We characterize the symmetric distributions that can be (approximately) generated by shallow Boolean circuits. More precisely, let $f\colon \{0,1\}^m \to \{0,1\}^n$ be a Boolean function where each output bit depends on at most $d$ input…

Computational Complexity · Computer Science 2025-11-19 Daniel M. Kane , Anthony Ostuni , Kewen Wu