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We consider random permutations on $\Sn$ with logarithmic growing cycles weights and study asymptotic behavior as the length $n$ tends to infinity. We show that the cycle count process converges to a vector of independent Poisson variables…

Probability · Mathematics 2018-06-14 Nicolas Robles , Dirk Zeindler

A joint limit theorem for the point process of the off-diagonal entries of a sample covariance matrix $\mathbf{S}$, constructed from $n$ observations of a $p$-dimensional random vector with iid components, and the Frobenius norm of…

Probability · Mathematics 2023-02-28 Johannes Heiny , Carolin Kleemann

This paper is concerned with the relationship of $y$-smooth integers and de Bruijn's approximation $\Lambda(x,y)$. Under the Riemann hypothesis, Saias proved that the count of $y$-smooth integers up to $x$, $\Psi(x,y)$, is asymptotic to…

Number Theory · Mathematics 2024-04-30 Ofir Gorodetsky

A permutation $\sigma$ of a multiset is called Stirling permutation if $\sigma(s)\ge \sigma(i)$ as soon as $\sigma(i)=\sigma(j)$ and $i<s<j.$ In our paper we study Stirling polynomials that arise in the generating function for descent…

Combinatorics · Mathematics 2013-08-27 Askar Dzhumadil'daev , Damir Yeliussizov

We consider real symmetric and complex Hermitian random matrices with the additional symmetry $h_{xy}=h_{N-x,N-y}$. The matrix elements are independent (up to the fourfold symmetry) and not necessarily identically distributed. This ensemble…

Mathematical Physics · Physics 2015-10-28 Johannes Alt

Alavi, Malde, Schwenk and Erd\H{o}s asked whether the independent set sequence of every tree is unimodal. Here we make some observations about this question. We show that for the uniformly random (labelled) tree, asymptotically almost…

Combinatorics · Mathematics 2021-07-06 Abdul Basit , David Galvin

By using the general framework of affine Gaudin models, we construct a new class of integrable sigma models. They are defined on a coset of the direct product of $N$ copies of a Lie group over some diagonal subgroup and they depend on…

High Energy Physics - Theory · Physics 2021-03-09 Gleb Arutyunov , Cristian Bassi , Sylvain Lacroix

For a set of dependent random variables, without stationary or the strong mixing assumptions, we derive the asymptotic independence between their sums and maxima. Then we apply this result to high-dimensional testing problems, where we…

Methodology · Statistics 2022-05-12 Long Feng , Tiefeng Jiang , Xiaoyun Li , Binghui Liu

We consider the joint distribution of eigenvalue clusters of the Wigner ensemble separated by macroscopic distances (i.e., on the same scale as the difference between the edges of the semicircle law). We prove that under an averaging…

Probability · Mathematics 2011-10-05 Yunjiang Jiang

The asymptotic behaviour of Linear Spectral Statistics (LSS) of the smoothed periodogram estimator of the spectral coherency matrix of a complex Gaussian high-dimensional time series $(\y_n)_{n \in \mathbb{Z}}$ with independent components…

Information Theory · Computer Science 2021-12-01 Philippe Loubaton , Alexis Rosuel

Delattre et al. (2013) considered n independent stochastic differential equations (SDEs), where in each case the drift term is associated with a random effect, the distribution of which depends upon unknown parameters. Assuming the…

Statistics Theory · Mathematics 2016-05-12 Trisha Maitra , Sourabh Bhattacharya

Gibbs sampling repeatedly samples from the conditional distribution of one variable, x_i, given other variables, either choosing i randomly, or updating sequentially using some systematic or random order. When x_i is discrete, a Gibbs…

Computation · Statistics 2024-03-28 Radford M. Neal

A new class of dependent random measures which we call {\it compound random measures} are proposed and the use of normalized versions of these random measures as priors in Bayesian nonparametric mixture models is considered. Their…

Methodology · Statistics 2015-09-03 Jim E. Griffin , Fabrizio Leisen

In this paper we study the asymptotics of linear regression in settings with non-Gaussian covariates where the covariates exhibit a linear dependency structure, departing from the standard assumption of independence. We model the covariates…

Machine Learning · Statistics 2024-12-10 Behrad Moniri , Hamed Hassani

This work prepares new probability bounds for sums of random, independent, Hermitian tensors. These probability bounds characterize large-deviation behavior of the extreme eigenvalue of the sums of random tensors. We extend Lapalace…

Probability · Mathematics 2021-01-01 Shih Yu Chang

It is well known that an extreme order statistic and a central order statistic (os) as well as an intermediate os and a central os from a sample of iid univariate random variables get asymptotically independent as the sample size increases.…

Statistics Theory · Mathematics 2017-02-01 Michael Falk , Florian Wisheckel

In this thesis we study convolutions that arise from noncommutative probability theory. We prove several regularity results for free convolutions, and for measures in partially defined one-parameter free convolution semigroups. We discuss…

Operator Algebras · Mathematics 2007-05-23 Serban Teodor Belinschi

We study asymptotic expansions in free probability. In a class of classical limit theorems Edgeworth expansion can be obtained via a general approach using sequences of "influence" functions of individual random elements described by…

Probability · Mathematics 2015-02-05 F. Götze , A. Reshetenko

In the seminal contribution [4] the joint weak convergence of maxima and minima of weakly dependent stationary sequences is derived under some mild asymptotic conditions. In this paper we address additionally the case of incomplete samples…

Probability · Mathematics 2014-10-08 Enkelejd Hashorva , Zhichao Weng

In a compound decision problem, consisting of $n$ statistically independent copies of the same problem to be solved under the sum of the individual losses, any reasonable compound decision rule $\delta$ satisfies a natural symmetry…

Statistics Theory · Mathematics 2019-12-02 Asaf Weinstein
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