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We show that as $n$ changes, the characteristic polynomial of the $n\times n$ random matrix with i.i.d. complex Gaussian entries can be described recursively through a process analogous to P\'olya's urn scheme. As a result, we get a random…

Probability · Mathematics 2015-09-25 Manjunath Krishnapur , Bálint Virág

This article studies the quasi-stationary behaviour of absorbed one-dimensional diffusions. We obtain necessary and sufficient conditions for the exponential convergence to a unique quasi-stationary distribution in total variation,…

Probability · Mathematics 2017-03-03 Nicolas Champagnat , Denis Villemonais

We prove a strong form of the equivalence of ensembles for the invariant measures of zero range processes conditioned to a supercritical density of particles. It is known that in this case there is a single site that accomodates a…

Probability · Mathematics 2009-12-08 Inés Armendáriz , Michail Loulakis

Recent work of Bornemann has uncovered hitherto hidden integrable structures relating to the asymptotic expansion of quantities at the soft edge of Gaussian and Laguerre random matrix ensembles. These quantities are spacing distributions…

Mathematical Physics · Physics 2026-04-10 Peter J. Forrester , Anas A. Rahman , Bo-Jian Shen

We develop a theory of insertion and deletion tolerance for point processes. A process is insertion-tolerant if adding a suitably chosen random point results in a point process that is absolutely continuous in law with respect to the…

Probability · Mathematics 2013-02-19 Alexander E. Holroyd , Terry Soo

Learning a distribution conditional on a set of discrete-valued features is a commonly encountered task. This becomes more challenging with a high-dimensional feature set when there is the possibility of interaction between the features. In…

Machine Learning · Statistics 2013-05-01 David C. Kessler , Jack Taylor , David B. Dunson

We study Spatial Logistic Gaussian Process (SLGP) models for non-parametric estimation of probability density fields using scattered samples of heterogeneous sizes. SLGPs are examined from the perspective of random measures and their…

Statistics Theory · Mathematics 2025-02-20 Athénaïs Gautier , David Ginsbourger

We study a physical system of $N$ interacting particles in $\mathbb{R}^d$, $d\geq1$, subject to pair repulsion and confined by an external field. We establish a large deviations principle for their empirical distribution as $N$ tends to…

Probability · Mathematics 2014-09-09 Djalil Chafaï , Nathael Gozlan , Pierre-André Zitt

The elliptic Ginibre ensemble of complex non-Hermitian random matrices allows to interpolate between the rotational invariant Ginibre ensemble and the Gaussian unitary ensemble of Hermitian random matrices. It corresponds to a…

Mathematical Physics · Physics 2023-02-09 G. Akemann , M. Duits , L. D. Molag

We continue the study of random continued fraction expansions, generated by random application of the Gauss and the R\'enyi backward continued fraction maps. We show that this random dynamical system admits a unique absolutely continuous…

Dynamical Systems · Mathematics 2021-10-13 Charlene Kalle , Valentin Matache , Masato Tsujii , Evgeny Verbitskiy

In this paper we show that the family P_d of probability distributions on R^d with log-concave densities satisfies a strong continuity condition. In particular, it turns out that weak convergence within this family entails (i) convergence…

Probability · Mathematics 2013-11-26 Dominic Schuhmacher , Andre Huesler , Lutz Duembgen

The paper considers probability distribution, density, conditional distribution and density and conditional moments as well as their kernel estimators in spaces of generalized functions. This approach does not require restrictions on…

Statistics Theory · Mathematics 2013-03-07 Victoria Zinde-Walsh

The probability density is a fundamental quantity for characterizing diffusion processes. However, it is seldom known except in a few renowned cases, including Brownian motion and the Ornstein-Uhlenbeck process and their bridges, geometric…

Mathematical Physics · Physics 2024-03-05 Alain Mazzolo

The paper is devoted to studying the image of probability measures on a Hilbert space under finite-dimensional analytic maps. We establish sufficient conditions under which the image of a measure has a density with respect to the Lebesgue…

Analysis of PDEs · Mathematics 2015-06-26 Andrei Agrachev , Sergei Kuksin , Andrey Sarychev , Armen Shirikyan

Recently the regular conditional distributions of max-infinitely divisible processes were derived by \citet{Dombry2011} and although these conditional distributions have complicated closed forms, \citet{Dombry2011b} introduce an algorithm…

Statistics Theory · Mathematics 2012-08-28 Clément Dombry , Mathieu Ribatet

Complex systems, and in particular random neural networks, are often described by randomly interacting dynamical systems with no specific symmetry. In that context, characterizing the number of relevant directions necessitates fine…

Probability · Mathematics 2014-03-10 Romain Allez , Jonathan Touboul , Gilles Wainrib

In numerous applications data are observed at random times and an estimated graph of the spectral density may be relevant for characterizing and explaining phenomena. By using a wavelet analysis, one derives a nonparametric estimator of the…

Statistics Theory · Mathematics 2009-11-27 Jean-Marc Bardet , Pierre Bertrand

We formulate and prove a very general relative version of the Dobrushin-Lanford-Ruelle theorem which gives conditions on constraints of configuration spaces over a finite alphabet such that for every absolutely summable relative…

Mathematical Physics · Physics 2020-05-07 Sebastián Barbieri , Ricardo Gómez , Brian Marcus , Siamak Taati

This paper is concerned with statistical inference for infinite range interaction Gibbs point processes and in particular for the large class of Ruelle superstable and lower regular pairwise interaction models. We extend classical…

Statistics Theory · Mathematics 2015-10-05 Jean-François Coeurjolly , Frédéric Lavancier

Consider a class of probability distributions which is dense in the space of all probability distributions on $\mathbb{R}^{d}$ with respect to weak convergence, for every $d\in\mathbb{N}$. Then, we construct various explicit classes of…

Probability · Mathematics 2020-12-03 Riccardo Passeggeri