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We are interested in estimating the location of what we call "smooth change-point" from $n$ independent observations of an inhomogeneous Poisson process. The smooth change-point is a transition of the intensity function of the process from…

Statistics Theory · Mathematics 2021-02-17 A. Amiri , S Dachian

Variational inference is a general framework to obtain approximations to the posterior distribution in a Bayesian context. In essence, variational inference entails an optimization over a given family of probability distributions to choose…

Statistics Theory · Mathematics 2025-07-24 Janis Keck

In this paper we establish an estimate for the rate of convergence of the Krasnosel'ski\v{\i}-Mann iteration for computing fixed points of non-expansive maps. Our main result settles the Baillon-Bruck conjecture [3] on the asymptotic…

Optimization and Control · Mathematics 2013-10-09 Roberto Cominetti , José A. Soto , José Vaisman

Using Stein's method and the Malliavin calculus of variations, we derive explicit estimates for the Gamma approximation of functionals of a Poisson measure. In particular, conditions are presented under which the distribution of a sequence…

Probability · Mathematics 2013-09-16 Giovanni Peccati , Christoph Thaele

In this paper, we aim to provide a statistical theory for object matching based on the Gromov-Wasserstein distance. To this end, we model general objects as metric measure spaces. Based on this, we propose a simple and efficiently…

Statistics Theory · Mathematics 2020-06-25 Christoph Alexander Weitkamp , Katharina Proksch , Carla Tameling , Axel Munk

We consider statistics on permutations chosen uniformly at random from fixed parabolic double cosets of the symmetric group. We show that the distribution of fixed points is asymptotically Poisson and establish central limit theorems for…

Probability · Mathematics 2023-04-20 J. E. Paguyo

In this paper, we study the inner and outer boundary densities of some sets with self-similar boundary having Minkowski dimension $s\textgreater{}d-1$ in $\mathbb{R}^{d}$. These quantities turn out to be crucial in some problems of set…

Probability · Mathematics 2016-08-07 Raphaël Lachièze-Rey , Sergio Vega

We refine the classical Lindeberg-Feller central limit theorem by obtaining asymptotic bounds on the Kolmogorov distance, the Wasserstein distance, and the parametrized Prokhorov distances in terms of a Lindeberg index. We thus obtain more…

Probability · Mathematics 2016-12-26 Ben Berckmoes , Geert Molenberghs

In this paper, we study the asymptotic behavior of a fully-coupled slow-fast McKean-Vlasov stochastic system. Using the non-linear Poisson equation on Wasserstein space, we first establish the strong convergence in the averaging principle…

Probability · Mathematics 2022-07-14 Yun Li , Longjie Xie

For a Borel set $A$ and a stationary Poisson point process $\eta_t$ in $\mathbb R^d$ of intensity $t>0$, the Poisson-Delaunay approximation $ A_{\eta_t}$ of $A$ is the union of all Delaunay cells generated by $\eta_t$ with center in $A$. It…

Probability · Mathematics 2024-10-31 Matthias Reitzner , Anna Strotmann

We develop the asymptotic expansion theory for vector-valued sequences (F N) N $\ge$1 of random variables in terms of the convergence of the Stein-Malliavin matrix associated to the sequence F N. Our approach combines the classical Fourier…

Probability · Mathematics 2017-12-11 Ciprian Tudor , Nakahiro Yoshida

The method of asymptotic expansions is used to build an approximation scheme relevant to celestial mechanics in relativistic theories of gravitation. A scalar theory is considered, both as a simple example and for its own sake. This theory…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Mayeul Arminjon

The aim of this article is to establish asymptotic distributions and consistency of subsampling for spectral density and for magnitude of coherence for non-stationary, almost periodically correlated time series. We show the asymptotic…

Statistics Theory · Mathematics 2011-02-11 Łukasz Lenart

We introduce a semi-parametric estimator of the Poisson intensity parameter of a spatial stationary Gibbs point process. Under very mild assumptions satisfied by a large class of Gibbs models, we establish its strong consistency and…

Statistics Theory · Mathematics 2013-08-14 Nadia Morsli , Jean-François Coeurjolly

We describe likelihood-based statistical tests for use in high energy physics for the discovery of new phenomena and for construction of confidence intervals on model parameters. We focus on the properties of the test procedures that allow…

Data Analysis, Statistics and Probability · Physics 2013-06-25 Glen Cowan , Kyle Cranmer , Eilam Gross , Ofer Vitells

We prove a parametric generalization of the classical Poincare-Perron theorem on stabilizing recurrence relations where we assume that the varying coefficients of a recurrence depend on auxiliary parameters and converge uniformly in these…

Functional Analysis · Mathematics 2010-11-10 J. Borcea , S. Friedland , B. Shapiro

We consider square-integrable functionals of Poisson point processes for which the variance upper bound provided by the classical Poincar\'{e} inequality is suboptimal, a phenomenon known as superconcentration. In this paper, we establish a…

Probability · Mathematics 2026-03-26 Chinmoy Bhattacharjee , Rowan O'Clarey

We study asymptotic behavior of orthogonal polynomials on the unit circle with varying Verblunsky coefficients $\alpha_{n,N}$ when the ratio $n/N$ converges as $n,N\to\infty$. First, we give a streamlined proof of ratio asymptotics for…

Classical Analysis and ODEs · Mathematics 2025-12-23 Rostyslav Kozhan , František Štampach

By combining the Malliavin calculus with Fourier techniques, we develop a high-order asymptotic expansion theory for a sequence of vector-valued random variables. Our asymptotic expansion formulas give the development of the characteristic…

Probability · Mathematics 2019-09-20 Ciprian Tudor , Nakahiro Yoshida

In this monograph, we prove an asymptotic approximation for integrals of probability densities over sets in finite dimensional euclidean space, which are far away from the origin (asymptotic sets). We use this approximation to investigate…

Probability · Mathematics 2009-09-29 Philippe Barbe