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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

In contrast to classical physics, the language of quantum mechanics involves operators and wave functions (or, more generally, density operators). However, in 1932, Wigner formulated quantum mechanics in terms of a distribution function…

Quantum Physics · Physics 2010-09-23 R. F. O'Connell

In this paper, we consider Bayesian inference on a class of multivariate median and the multivariate quantile functionals of a joint distribution using a Dirichlet process prior. Since, unlike univariate quantiles, the exact posterior…

Statistics Theory · Mathematics 2021-06-03 Indrabati Bhattacharya , Subhashis Ghosal

One of the main research areas in Bayesian Nonparametrics is the proposal and study of priors which generalize the Dirichlet process. Here we exploit theoretical properties of Poisson random measures in order to provide a comprehensive…

Statistics Theory · Mathematics 2007-06-13 Lancelot F. James , Antonio Lijoi , Igor Pruenster

We analyze the form of the probability distribution function P_{n}^{(\beta)}(w) of the Schmidt-like random variable w = x_1^2/(\sum_{j=1}^n x^{2}_j/n), where x_j are the eigenvalues of a given n \times n \beta-Gaussian random matrix, \beta…

Disordered Systems and Neural Networks · Physics 2015-06-11 M. P. Pato , G. Oshanin

In this paper we use probabilistic methods to derive some results on the generalized Bernoulli and generalized Euler polynomials. Our approach is based on the properties of Appell polynomials associated with uniformly distributed and…

Probability · Mathematics 2013-07-18 Bao Quoc Ta

We consider the problem of estimating the missing mass, partition function or evidence and its probability distribution in the case that for each sample point in the discrete sample space its (unnormalized) probability mass is revealed.…

Statistics Theory · Mathematics 2026-03-16 Bastiaan J. Braams

In this thesis, we investigate the asymptotics of random partitions chosen according to probability measures coming from the representation theory of the symmetric groups $S_n$ and of the finite Chevalley groups $GL(n,F_q)$ and…

Representation Theory · Mathematics 2010-12-21 Pierre-Loïc Méliot

Multiple orthogonal polynomials are a generalization of orthogonal polynomials in which the orthogonality is distributed among a number of orthogonality weights. They appear in random matrix theory in the form of special determinantal point…

Classical Analysis and ODEs · Mathematics 2015-01-20 Arno B. J. Kuijlaars

Conway-Maxwell-Poisson (CMP) distributions are flexible generalizations of the Poisson distribution for modelling overdispersed or underdispersed counts. The main hindrance to their wider use in practice seems to be the inability to…

Methodology · Statistics 2017-02-15 Alan Huang

We study two functionals of a random matrix $\boldsymbol A$ with independent elements uniformly distributed over the cyclic group of integers $\{0,1,\ldots, M-1\}$ modulo $M$. One of them, $V_0(\boldsymbol A)$ with mean $\mu$, gives the…

Probability · Mathematics 2015-07-21 Alexey Lindo , Serik Sagitov

Let $\{{\bf \mathcal{Z}}_n:n\geq 1\}$ be a sequence of i.i.d. random probability measures. Independently, for each $n\geq 1$, let $(X_{n1},\ldots, X_{nn})$ be a random vector of positive random variables that add up to one. This paper…

Probability · Mathematics 2021-06-24 Shui Feng

Macroscopic mechanical properties of polymers are determined by their microscopic molecular chain distribution. Due to randomness of these molecular chains, probability theory has been used to find their micro-states and energy…

Statistical Mechanics · Physics 2023-08-23 Lixiang Yang

We study the partition function from random matrix theory using a well known connection to orthogonal polynomials, and a recently developed Riemann-Hilbert approach to the computation of detailed asymptotics for these orthogonal…

Mathematical Physics · Physics 2007-05-23 N. M. Ercolani , K. D. T-R McLaughlin

We prove some "high probability" results on the expected value of the mean width for random perturbations of random polytopes. The random perturbations are considered for Gaussian and $p$-stable random vectors, as well as uniform…

Functional Analysis · Mathematics 2013-03-25 David Alonso-Gutierrez , Joscha Prochno

This paper first surveys the connection of integrable systems of the Painleve type to various distribution functions appearing in Wigner-Dyson random matrix theory. A short discussion is then given of the appearance of these same…

solv-int · Physics 2007-05-23 Craig A. Tracy , Harold Widom

An integer partition of $n$ is a decreasing sequence of positive integers that add up to $[n]$. Back in $1979$ Macdonald posed a question about the limit value of the probability that two partitions chosen uniformly at random, and…

Combinatorics · Mathematics 2018-03-13 Boris Pittel

Experiments involving single or few elementary particles are completely described by Quantum Mechanics. Notwithstanding the success of that quantitative description, various aspects of observations, as nonlocality and the statistical…

Quantum Physics · Physics 2016-02-26 Martine Chevrollier , Marcos Oriá

Convergence of order $O(1/\sqrt{n})$ is obtained for the distance in total variation between the Poisson distribution and the distribution of the number of fixed size cycles in generalized random graphs with random vertex weights. The…

Probability · Mathematics 2024-05-31 Sergey G. Bobkov , Maria A. Danshina , Vladimir V. Ulyanov

The two parameter Poisson-Dirichlet distribution $PD(\alpha,\theta)$ is the distribution of an infinite dimensional random discrete probability. It is a generalization of Kingman's Poisson-Dirichlet distribution. The two parameter Dirichlet…

Probability · Mathematics 2009-03-22 Shui Feng , Wei Sun
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