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This paper is concerned with Spearman's correlation matrices under large dimensional regime, in which the data dimension diverges to infinity proportionally with the sample size. We establish the central limit theorem for the linear…

Statistics Theory · Mathematics 2024-11-26 Hantao Chen , Cheng Wang

We investigate the number of integer solutions to a multiplicative Diophantine approximation problem and show that the associated counting function converges in distribution to a normal law. Our approach relies on the analysis of…

Number Theory · Mathematics 2026-01-21 Michael Björklund , Reynold Fregoli , Alexander Gorodnik

In this note, we give a probabilistic interpretation of the Central Limit Theorem used for approximating isotropic Gaussians in [1].

Information Theory · Computer Science 2011-09-29 Kunal Narayan Chaudhury

In applied probability, the normal approximation is often used for the distribution of data with assumed additive structure. This tradition is based on the central limit theorem for sums of (independent) random variables. However, it is…

Probability · Mathematics 2020-10-27 Alexandra Dorofeeva , Victor Korolev , Alexander Zeifman

We obtain some sufficient conditions for the Central Limit Theorem for the random processes (fields) with values in the separable part of Holder space in the modern terms of majorizing (minorizing) measures, belonging to X.Fernique and…

Probability · Mathematics 2014-09-23 E. Ostrovsky , L. Sirota

We consider eigenvalues of generalized Wishart processes as well as particle systems, of which the empirical measures converge to deterministic measures as the dimension goes to infinity. In this paper, we obtain central limit theorems to…

Probability · Mathematics 2019-08-12 Jian Song , Jianfeng Yao , Wangjun Yuan

We consider multiple and set-indexed sums of random vectors taking values in Euclidean space of growing dimension. It is shown that, when viewed as finite metric spaces, the sets of values of such sums converge in probability. The limit is…

Probability · Mathematics 2026-05-18 Bochen Jin , Alexander Marynych , Ilya Molchanov

We introduce a simple instance of the renormalization group transformation in the Banach space of probability densities. By changing the scaling of the renormalized variables we obtain, as fixed points of the transformation, the L\'evy…

Mathematical Physics · Physics 2016-08-14 I. Calvo , J. C. Cuchí , J. G. Esteve , F. Falceto

Quantitative bounds for random embeddings of $\mathbb{R}^{k}$ into Lorentz sequence spaces are given, with improved dependence on $\varepsilon$.

Functional Analysis · Mathematics 2021-04-27 Daniel J. Fresen

In our previous paper \cite{FTD1}, we derived the almost sure convergence of the global density of eigenvalues of random matrices of the SYK model. In this paper, we will prove the central limit theorem for the linear statistic of…

Mathematical Physics · Physics 2018-06-18 Renjie Feng , Gang Tian , Dongyi Wei

In Part I of this article (Banerjee and Kuchibhotla (2023)), we have introduced a new method to bound the difference in expectations of an average of independent random vector and the limiting Gaussian random vector using level sets. In the…

Probability · Mathematics 2023-06-27 Arun Kumar Kuchibhotla

Quasiconformal homeomorphisms of the whole space Rn, onto itself normalized at one or two points are studied. In particular, the stability theory, the case when the maximal dilatation tends to 1, is in the focus. Our main result provides a…

Complex Variables · Mathematics 2017-08-15 R. Klén , V. Todorčević , M. Vuorinen

We introduce a class of Boltzmann equations on the real line, which constitute extensions of the classical Kac caricature. The collisional gain operators are defined by smoothing transformations with quite general properties. By…

Probability · Mathematics 2008-10-16 Federico Bassetti , Lucia Ladelli , Daniel Matthes

In this paper, explicit error bounds are derived in the approximation of rank $k$ projections of certain $n$-dimensional random vectors by standard $k$-dimensional Gaussian random vectors. The bounds are given in terms of $k$, $n$, and a…

Probability · Mathematics 2007-06-07 Elizabeth Meckes

We study the Central Limit Theorem (CLT) in the so-called mixed (anisotropic) Lebesgue-Riesz spaces and tail behavior of normed sums of centered random independent variables (vectors) with values in these spaces.

Probability · Mathematics 2013-08-27 E. Ostrovsky , L. Sirota

Quantitative multivariate central limit theorems for general functionals of possibly non-symmetric and non-homogeneous infinite Rademacher sequences are proved by combining discrete Malliavin calculus with the smart path method for normal…

Probability · Mathematics 2017-11-06 Kai Krokowski , Christoph Thaele

Central limit theorems (CLTs) for high-dimensional random vectors with dimension possibly growing with the sample size have received a lot of attention in the recent times. Chernozhukov et al. (2017) proved a Berry--Esseen type result for…

Statistics Theory · Mathematics 2019-06-26 Arun Kumar Kuchibhotla , Somabha Mukherjee , Debapratim Banerjee

Non-asymptotic bounds for Gaussian and bootstrap approximation have recently attracted significant interest in high-dimensional statistics. This paper studies Berry-Esseen bounds for such approximations with respect to the multivariate…

Statistics Theory · Mathematics 2022-02-08 Miles E. Lopes

We study the generalized scalar tensor theory with a potential in the Bianchi type I model by using the ADM formalism. We examine the conditions for the Universe to be in expansion, isotropic and with a positive potential at late time in…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Stephane Fay

The discounted central limit theorem concerns the convergence of an infinite discounted sum of i.i.d. random variables to normality as the discount factor approaches $1$. We show that, using the Fourier metric on probability distributions,…

Probability · Mathematics 2018-11-12 Guy Katriel