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Consider a set of multivariate distributions, $F_1,\dots,F_M$, aiming to explain the same phenomenon. For instance, each $F_m$ may correspond to a different candidate background model for calibration data, or to one of many possible signal…

Methodology · Statistics 2022-04-06 Sara Algeri

We investigate joint spectral characteristics of a family of matrices $\mathcal F $, associated with products in the semigroup generated by $\mathcal F$. In the literature, extremal measures such as the well-known joint spectral radius and…

Dynamical Systems · Mathematics 2026-04-27 Francesco Paolo Maiale , Anastasiia Trofimova , Nicola Guglielmi

We consider sample covariance matrices $S_N=\frac{1}{p}\Sigma_N^{1/2}X_NX_N^* \Sigma_N^{1/2}$ where $X_N$ is a $N \times p$ real or complex matrix with i.i.d. entries with finite $12^{\rm th}$ moment and $\Sigma_N$ is a $N \times N$…

Probability · Mathematics 2009-11-17 Olivier Ledoit , Sandrine Péché

Let $G$ be a finitely generated group equipped with a finite symmetric generating set and the associated word length function $|\cdot |$. We study the behavior of the probability of return for random walks driven by symmetric measures $\mu$…

Probability · Mathematics 2015-01-26 Laurent Saloff-Coste , Tianyi Zheng

We show that the fluctuations of the linear eigenvalue statistics of a non-Hermitian random band matrix of increasing bandwidth $b_{n}$ with a continuous variance profile $w_{\nu}(x)$ converges to a $N(0,\sigma_{f}^{2}(\nu))$, where…

Probability · Mathematics 2023-06-30 Indrajit Jana

Let $\{X, X_{n}; n \geq 1\}$ be a sequence of i.i.d. non-degenerate real-valued random variables with $\mathbb{E}X^{2} < \infty$. Let $S_{n} = \sum_{i=1}^{n} X_{i}$, $n \geq 1$. Let $g(\cdot): ~[0, \infty) \rightarrow [0, \infty)$ be a…

Probability · Mathematics 2025-05-02 Deli Li , Yu Miao , Yongcheng Qi

Skewness measures can be used to measure the level of asymmetry of a distribution. Given the prevalence of statistical methods that assume underlying symmetry, and also the desire for symmetry in order to make meaningful judgements for…

Statistics Theory · Mathematics 2019-12-19 Chandima N. P. G. Arachchige , Luke A. Prendergast

This paper studies the problem of estimating a covariance matrix from correlated sub-Gaussian samples. We consider using the correlated sample covariance matrix estimator to approximate the true covariance matrix. We establish…

Information Theory · Computer Science 2019-10-17 Xu Zhang , Wei Cui , Yulong Liu

In this paper, we investigate the precise local large deviation probabilities for random sums of independent real-valued random variables with a common distribution $F$, where $F(x+\Delta)=F((x, x+T])$ is an $\mathcal{O}$-regularly varying…

Probability · Mathematics 2016-07-05 Qiuying Zhang , Fengyang Cheng

We consider the least-squares regression problem and provide a detailed asymptotic analysis of the performance of averaged constant-step-size stochastic gradient descent (a.k.a. least-mean-squares). In the strongly-convex case, we provide…

Machine Learning · Computer Science 2014-12-02 Alexandre Défossez , Francis Bach

A classical problem of statistical inference is the valid specification of a model that can account for the statistical dependencies between observations when the true structure is dense, intractable, or unknown. To address this problem, a…

Statistics Theory · Mathematics 2023-10-19 Shane Sparkes , Lu Zhang

Given a parametric polynomial curve $\gamma:[a,b]\rightarrow \mathbb{R}^n$, how can we sample a random point $\mathfrak{x}\in \mathrm{im}(\gamma)$ in such a way that it is distributed uniformly with respect to the arc-length? Unfortunately,…

Computational Geometry · Computer Science 2022-09-28 Apostolos Chalkis , Christina Katsamaki , Josué Tonelli-Cueto

We derive a simple and precise approximation to probability density functions in sampling distributions based on the Fourier cosine series. After clarifying the required conditions, we illustrate the approximation on two examples: the…

Statistics Theory · Mathematics 2021-04-27 Shigekazu Nakagawa , Hiroki Hashiguchi , Yoko Ono

For each $n$, let $A_n=(\sigma_{ij})$ be an $n\times n$ deterministic matrix and let $X_n=(X_{ij})$ be an $n\times n$ random matrix with i.i.d. centered entries of unit variance. In the companion article Cook et al., we considered the…

Probability · Mathematics 2020-07-31 Nicholas A. Cook , Walid Hachem , Jamal Najim , David Renfrew

We analyze the asymptotic fluctuations of linear eigenvalue statistics of random centrosymmetric matrices with i.i.d. entries. We prove that for a complex analytic test function, the centered and normalized linear eigenvalue statistics of…

Probability · Mathematics 2025-10-20 Indrajit Jana , Sunita Rani

The scaled standard Wigner matrix (symmetric with mean zero, variance one i.i.d. entries), and its limiting eigenvalue distribution, namely the semi-circular distribution, has attracted much attention. The $2k$th moment of the limit equals…

Probability · Mathematics 2021-03-18 Arup Bose , Koushik Saha , Arusharka Sen , Priyanka Sen

We establish the rate of convergence of distributions of sums of independent identically distributed random variables to the Gaussian distribution in terms of truncated pseudomoments by implementing the idea of Yu. Studnyev for getting…

Probability · Mathematics 2015-08-13 Yuliya Mishura , Yevheniya Munchak , Petro Slyusarchuk

The general relationship between an arbitrary frequency distribution and the expectation value of the frequency distributions of its samples is esablished. A set of combinations of expectation values whose value does not in general depend…

Data Analysis, Statistics and Probability · Physics 2012-10-05 Paolo Rossi

We focus on the time-varying modeling of VaR at a given coverage $\tau$, assessing whether the quantiles of the distribution of the returns standardized by their conditional means and standard deviations exhibit predictable dynamics. Models…

Risk Management · Quantitative Finance 2023-06-01 Fabrizio Cipollini , Giampiero M. Gallo , Alessandro Palandri

Semiparametric estimators admitting a von Mises expansion often reduce inference to the influence-function variance. This reduction is justified when the second-order remainder is negligible in variance, a condition that is stronger than…

Methodology · Statistics 2026-05-26 Lin Li , Pengcheng Wu