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We show that the Riemannian Gaussian distributions on symmetric spaces, introduced in recent years, are of standard random matrix type. We exploit this to compute analytically marginals of the probability density functions. This can be done…

Mathematical Physics · Physics 2021-10-29 Leonardo Santilli , Miguel Tierz

In this work we study the estimation of the density of a totally positive random vector. Total positivity of the distribution of a random vector implies a strong form of positive dependence between its coordinates and, in particular, it…

Statistics Theory · Mathematics 2023-05-10 Ali Zartash , Elina Robeva

This paper is devoted to a study of $S$-curves, that is systems of curves in the complex plane whose equilibrium potential in a harmonic external field satisfies a special symmetry property ($S$-property). Such curves have many…

Complex Variables · Mathematics 2011-12-30 E. A. Rakhmanov

Rank 1 inhomogeneous random graphs are a natural generalization of Erd\H{o}s R\'enyi random graphs. In this generalization each node is given a weight. Then the probability that an edge is present depends on the product of the weights of…

Probability · Mathematics 2021-07-28 Othmane Safsafi

We consider polynomials $P_n$ orthogonal with respect to the weight $J_{\nu}$ on $[0,\infty)$, where $J_{\nu}$ is the Bessel function of order $\nu$. Asheim and Huybrechs considered these polynomials in connection with complex Gaussian…

Classical Analysis and ODEs · Mathematics 2019-03-22 Alfredo Deaño , Arno B. J. Kuijlaars , Pablo Román

In Bayesian theory, calculating a posterior probability distribution is highly important but usually difficult. Therefore, some methods have been put forward to deal with such problem, among which, the most popular one is the asymptotic…

Methodology · Statistics 2012-07-20 Zai-Ying Zhou

Strongly non-Gaussian ensembles of large random matrices possessing unitary symmetry and logarithmic level repulsion are studied both in presence and absence of hard edge in their energy spectra. Employing a theory of polynomials orthogonal…

Condensed Matter · Physics 2009-10-28 V. Freilikher , E. Kanzieper , I. Yurkevich

For systems of equations with an infinite set of roots, one can sometimes obtain Kushnirenko-Bernstein-Khovanskii type theorem if replace the number of roots by their asymptotic density. We consider systems of entire functions with…

Complex Variables · Mathematics 2023-12-12 B. Kazarnovskii

We determine the asymptotics for the variance of the number of zeros of random linear combinations of orthogonal polynomials of degree $\leq n$ in subintervals $\left [ a,b\right ] $ of the support of the underlying orthogonality measure…

Probability · Mathematics 2021-01-19 Doron S. Lubinsky , Igor E. Pritsker

Asymptotic expansions are derived for Gegenbauer (ultraspherical) polynomials for large order $n$ that are uniformly valid for unbounded complex values of the argument $z$, including the real interval $0 \leq z \leq 1$ in which the zeros in…

Classical Analysis and ODEs · Mathematics 2025-07-04 T. M. Dunster

Asymptotic approximations of Jacobi polynomials are given in terms of elementary functions for large degree $n$ and parameters $\alpha$ and $\beta$. From these new results, asymptotic expansions of the zeros are derived and methods are…

Classical Analysis and ODEs · Mathematics 2020-07-22 Amparo Gil , Javier Segura , Nico M. Temme

We establish some asymptotic expansions for infinite weighted convolutions of distributions having light subexponential tails. Examples are presented, some showing that in order to obtain an expansion with two significant terms, one needs…

Probability · Mathematics 2007-06-13 Ph. Barbe , W. P. McCormick

We study the convergence of a random iterative sequence of a family of operators on infinite dimensional Hilbert spaces, inspired by the Stochastic Gradient Descent (SGD) algorithm in the case of the noiseless regression, as studied in [1].…

Functional Analysis · Mathematics 2022-09-02 Soumyadip Ghosh , Yingdong Lu , Tomasz J. Nowicki

Let $X_1,X_2,\ldots$ be independent and identically distributed random variables in $\mathbb{C}$ chosen from a probability measure $\mu$ and define the random polynomial $$ P_n(z)=(z-X_1)\ldots(z-X_n)\,. $$ We show that for any sequence $k…

Probability · Mathematics 2022-12-23 Marcus Michelen , Xuan-Truong Vu

The asymptotic analysis of covariance parameter estimation of Gaussian processes has been subject to intensive investigation. However, this asymptotic analysis is very scarce for non-Gaussian processes. In this paper, we study a class of…

Statistics Theory · Mathematics 2019-11-27 François Bachoc , José Bétancourt , Reinhard Furrer , Thierry Klein

We consider random polynomials whose coefficients are independent and identically distributed on the integers. We prove that if the coefficient distribution has bounded support and its probability to take any particular value is at most…

Probability · Mathematics 2017-02-07 Ohad N. Feldheim , Arnab Sen

We use a non-linear characterization of orthonormal polynomials due to Saff in order to show that the behavior of orthonormal polynomials is determined only by its leading coefficient and its normalization. Several applications of this…

Spectral Theory · Mathematics 2021-08-11 Brian Simanek

We generalize some previous results on random polynomials in several complex variables. A standard setting is to consider random polynomials $H_n(z):=\sum_{j=1}^{m_n} a_jp_j(z)$ that are linear combinations of basis polynomials $\{p_j\}$…

Complex Variables · Mathematics 2024-01-29 Turgay Bayraktar , Tom Bloom , Norm Levenberg

We study the number of real roots of a Kostlan random polynomial of degree $d$ in one variable. More generally, we are interested in the distribution of the counting measure of the set of real roots of such a polynomial. We compute the…

Algebraic Geometry · Mathematics 2021-12-09 Michele Ancona , Thomas Letendre

Uncovering genuine relationships between a response variable of interest and a large collection of covariates is a fundamental and practically important problem. In the context of Gaussian linear models, both the Bayesian and non-Bayesian…

Statistics Theory · Mathematics 2025-04-11 Jeyong Lee , Minwoo Chae , Ryan Martin