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The functional linear model extends the notion of linear regression to the case where the response and covariates are iid elements of an infinite dimensional Hilbert space. The unknown to be estimated is a Hilbert-Schmidt operator, whose…

Statistics Theory · Mathematics 2016-12-22 Tung Pham , Victor Panaretos

This paper aims to establish a central limit theorem for Markov processes conditioned not to be absorbed under a very general assumption on quasi-stationarity for the underlying process. To do so, a central limit theorem has been…

Probability · Mathematics 2023-03-31 William Oçafrain

We obtain a Gessel-type expansion in Jack polynomials for the expectations of multiplicative functionals in the circular $\beta$-ensemble. As a consequence, we establish a Szeg\H{o}-type limit theorem for all $H^{1/2}(\mathbb{T})$ functions…

Probability · Mathematics 2026-04-14 Sergei M. Gorbunov

For testing hypothesis on the covariance operator of functional time series, we suggest to use the full functional information and to avoid dimension reduction techniques. The limit distribution follows from the central limit theorem of the…

Statistics Theory · Mathematics 2020-03-02 Olimjon Sh. Sharipov , Martin Wendler

In this paper, we discuss the joint value distribution of $L$-functions in a suitable class. We obtain joint large deviations results in the central limit theorem for these $L$-functions and some mean value theorems, which give evidence…

Number Theory · Mathematics 2021-02-26 Shōta Inoue , Junxian Li

This paper focuses on limit theorems for linear Hawkes processes with random marks. We prove a large deviation principle, which answers the question raised by Bordenave and Torrisi. A central limit theorem is also obtained. We conclude with…

Probability · Mathematics 2015-09-15 Dmytro Karabash , Lingjiong Zhu

A Central Limit Theorem for linear combinations of iterates of an inner function is proved. The main technical tool is Aleksandrov Desintegration Theorem for Aleksandrov-Clark measures.

Complex Variables · Mathematics 2020-06-23 Artur Nicolau , Odí Soler i Gibert

We prove a multidimensional extension of Selberg's central limit theorem for the logarithm of the Riemann zeta function on the critical line. The limit is a totally disordered process, whose coordinates are all independent and Gaussian.

Probability · Mathematics 2007-05-23 C. P. Hughes , A. Nikeghbali , M. Yor

In this paper we study supercritical super-OU processes with general branching mechanisms satisfying a second moment condition. We establish central limit theorems for the super-OU processes. In the small and crtical branching rate cases,…

Probability · Mathematics 2013-02-07 Yan-Xia Ren , Renming Song , Rui Zhang

In this note, we introduce a novel norm, termed the $t-$Berezin norm, on the algebra of all bounded linear operators defined on a reproducing kernel Hilbert space $\mathcal{H}$ as $$\|A\|_{t-ber} = \sup_{ \lambda, \mu \in \Omega} \left\{…

Functional Analysis · Mathematics 2025-04-10 Raj Kumar Nayak , Pintu Bhunia

We present limit theorems for a sequence of Piecewise Deterministic Markov Processes (PDMPs) taking values in a separable Hilbert space. This class of processes provides a rigorous framework for stochastic spatial models in which discrete…

Probability · Mathematics 2012-04-13 Martin G. Riedler , Michèle Thieullen , Gilles Wainrib

Let $(p_k)_{k\in\mathbb{N}}$ be a discrete probability distribution for which the counting function $x\mapsto \#\{k\in\mathbb{N}: p_k\geq 1/x\}$ belongs to the de Haan class $\Pi$. Consider a deterministic weighted branching process…

Probability · Mathematics 2021-04-15 Alexander Iksanov , Zakhar Kabluchko , Valeriya Kotelnikova

We consider a class of self-similar, continuous Gaussian processes that do not necessarily have stationary increments. We prove a version of the Breuer-Major theorem for this class, that is, subject to conditions on the covariance function,…

Probability · Mathematics 2016-12-06 Daniel Harnett , David Nualart

We prove a functional limit theorem in a space of analytic functions for the random Dirichlet series $D(\alpha;z)=\sum_{n\geq 2}(\log n)^{\alpha}(\eta_n+{\rm i} \theta_n)/n^z$, properly scaled and normalized, where…

Probability · Mathematics 2022-11-02 Dariusz Buraczewski , Congzao Dong , Alexander Iksanov , Alexander Marynych

In this paper, we investigate the functional central limit theorem for stochastic processes associated to partial sums of additive functionals of reversible Markov chains with general spate space, under the normalization standard deviation…

Probability · Mathematics 2022-08-02 Magda Peligrad , Sergey Utev

We provide a detailed description of the model Hilbert space $L^2(\bbR; d\Sigma; \cK)$, were $\cK$ represents a complex, separable Hilbert space, and $\Sigma$ denotes a bounded operator-valued measure. In particular, we show that several…

Spectral Theory · Mathematics 2011-11-04 Fritz Gesztesy , Rudi Weikard , Maxim Zinchenko

In this article, we prove the following spectral theorem for right linear normal operators (need not to be bounded) in quaternionic Hilbert spaces: Let $T$ be an unbounded right quaternionic linear normal operator in a quaternionic Hilbert…

Spectral Theory · Mathematics 2017-11-07 G. Ramesh , P. Santhosh Kumar

Let $X_n=\sum_{i=1}^{\infty}a_i\epsilon_{n-i}$, where the $\epsilon_i$ are i.i.d. with mean 0 and at least finite second moment, and the $a_i$ are assumed to satisfy $|a_i|=O(i^{-\beta})$ with $\beta >1/2$. When $1/2<\beta<1$, $X_n$ is…

Statistics Theory · Mathematics 2008-12-18 Tsung-Lin Cheng , Hwai-Chung Ho

Functional analysis, especially the theory of Hilbert spaces and of operators on these, form an important area in mathematics. We formalized the Isabelle/HOL library Complex_Bounded_Operators containing a large amount of theorems about…

Logic in Computer Science · Computer Science 2025-12-08 Dominique Unruh , José Manuel Rodríguez Caballero

We discuss various theorems about bounded analytic functions on the bidisk that were proved using operator theory.

Complex Variables · Mathematics 2009-01-08 Jim Agler , John McCarthy