papers

Publications (53)

math.PR2014

Integration by parts and representation of information functionals

Ivan Nourdin, Giovanni Peccati, Yvik Swan

We introduce a new formalism for computing expectations of functionals of arbitrary random vectors, by using generalised integration by parts formulae. In doing so we extend recent…

math.PR2022

A note on one-dimensional Poincaré inequalities by Stein-type integration

Gilles Germain, Yvik Swan

We study the weighted Poincaré constant of a probability density with weight function using integration methods inspired by Stein's method. We obtain a new versio…

math.PR2021

Stein's method and approximating the multidimensional quantum harmonic oscillator

Ian W. McKeague, Yvik Swan

Stein's method is used to study discrete representations of multidimensional distributions that arise as approximations of states of quantum harmonic oscillators. These representat…

math.PR2016

Stein's method for comparison of univariate distributions

Christophe Ley, Gesine Reinert, Yvik Swan

We propose a new general version of Stein's method for univariate distributions. In particular we propose a canonical definition of the Stein operator of a probability distribution…

math.PR2019

Stein operators, kernels and discrepancies for multivariate continuous distributions

Guillaume Mijoule, Gesine Reinert, Yvik Swan

In this paper we present a general framework for Stein's method for multivariate continuous distributions. The approach gives a collection of Stein characterisations, among which w…

stat.ME2012

One-Step R-Estimation in Linear Models with Stable Errors

Marc Hallin, Yvik Swan, Thomas Verdebout +1

Classical estimation techniques for linear models either are inconsistent, or perform rather poorly, under -stable error densities; most of them are not even rate-optimal. In t…

math.PR2013

Parametric Stein operators and variance bounds

Christophe Ley, Yvik Swan

Stein operators are differential operators which arise within the so-called Stein's method for stochastic approximation. We propose a new mechanism for constructing such operators…

math.ST2024

Stein's Method of Moments

Bruno Ebner, Adrian Fischer, Robert E. Gaunt +2

Stein operators allow to characterise probability distributions via differential operators. Based on these characterisations, we develop a new method of point estimation for margin…

math.PR2016

A stroll along the gamma

Benjamin Arras, Yvik Swan

We provide the first in-depth study of the "smart path" interpolation between an arbitrary probability measure and the gamma- distribution. We propose new explicit repres…

math.PR2018

An algebra of Stein operators

Robert E. Gaunt, Guillaume Mijoule, Yvik Swan

We build upon recent advances on the distributional aspect of Stein's method to propose a novel and flexible technique for computing Stein operators for random variables that can b…

stat.ML2025

Split Conformal Prediction under Data Contamination

Jase Clarkson, Wenkai Xu, Mihai Cucuringu +2

Conformal prediction is a non-parametric technique for constructing prediction intervals or sets from arbitrary predictive models under the assumption that the data is exchangeable…

math.PR2013

Rates of convergence towards the Fréchet distribution

Carine Bartholmé, Yvik Swan

We develop Stein's method for the Fréchet distribution and apply it to compute rates of convergence in distribution of renormalized sample maxima to the Fréchet distribution.

cs.DS2019

The Adaptive Sampling Revisited

Matthew Drescher, Guy Louchard, Yvik Swan

The problem of estimating the number of distinct keys of a large collection of data is well known in computer science. A classical algorithm is the adaptive sampling (AS).…

math.ST2012

Efficient ANOVA for directional data

Christophe Ley, Yvik Swan, Thomas Verdebout

In this paper we tackle the ANOVA problem for directional data (with particular emphasis on geological data) by having recourse to the Le Cam methodology usually reserved for linea…

math.PR2013

Stein's density approach and information inequalities

Christophe Ley, Yvik Swan

We provide a new perspective on Stein's so-called density approach by introducing a new operator and characterizing class which are valid for a much wider family of probability dis…

stat.AP2012

Optimal R-Estimation of a Spherical Location

Christophe Ley, Yvik Swan, Baba Thiam +1

In this paper, we provide -estimators of the location of a rotationally symmetric distribution on the unit sphere of . In order to do so we first prove the local asymptoti…

math.PR2017

A bound on the 2-Wasserstein distance between linear combinations of independent random variables

Benjamin Arras, Ehsan Azmoodeh, Guillaume Poly +1

We provide a bound on a natural distance between finitely and infinitely supported elements of the unit sphere of , the space of real valued sequences with fi…

math.PR2017

A new approach to the Stein-Tikhomirov method: with applications to the second Wiener chaos and Dickman convergence

Benjamin Arras, Guillaume Mijoule, Guillaume Poly +1

In this paper, we propose a general means of estimating the rate at which convergences in law occur. Our approach, which is an extension of the classical Stein-Tikhomirov method, r…

math.PR2016

On the rate of convergence in de Finetti's representation theorem

Guillaume Mijoule, Giovanni Peccati, Yvik Swan

A consequence of de Finetti's representation theorem is that for every infinite sequence of exchangeable 0-1 random variables , there exists a probability measure $…

math.PR2023

One-dimensional Stein's method with bespoke derivatives

Gilles Germain, Yvik Swan

We introduce a version of Stein's method of comparison of operators specifically tailored to the problem of bounding the Wasserstein-1 distance between continuous and discrete dist…

cs.IT2024

Derivatives of entropy and the MMSE conjecture

Paul Mansanarez, Guillaume Poly, Yvik Swan

We investigate the entropy of a probability measure along the heat flow and more precisely we seek for closed algebraic representations of its derivatives. Provided…

math.PR2025

Edgeworth expansion on Wiener chaos

Paul Mansanarez, Guillaume Poly, Yvik Swan

Consider an element of the -th Wiener chaos $\WW_p$, and denote by $\prob_F$ its law. For a positive integer , let be the Radon measure with density…

math.PR2016

Stein's method on the second Wiener chaos : 2-Wasserstein distance

Benjamin Arras, Ehsan Azmoodeh, Guillaume Poly +1

In the first part of the paper we use a new Fourier technique to obtain a Stein characterizations for random variables in the second Wiener chaos. We provide the connection between…

math.PR2013

Entropy and the fourth moment phenomenon

Ivan Nourdin, Giovanni Peccati, Yvik Swan

We develop a new method for bounding the relative entropy of a random vector in terms of its Stein factors. Our approach is based on a novel representation for the score function o…

math.PR2011

On a connection between Stein characterizations and Fisher information

Christophe Ley, Yvik Swan

We generalize the so-called density approach to Stein characterizations of probability distributions. We prove an elementary factorization property of the resulting Stein operator…

math.PR2019

Some new Stein operators for product distributions

Robert E. Gaunt, Guillaume Mijoule, Yvik Swan

We provide a general result for finding Stein operators for the product of two independent random variables whose Stein operators satisfy a certain assumption, extending a recent r…

math.ST2013

On Hodges and Lehmann's " result"

Marc Hallin, Thomas Verdebout, Yvik Swan

While the asymptotic relative efficiency (ARE) of Wilcoxon rank-based tests for location and regression with respect to their parametric Student competitors can be arbitrarily larg…

math.PR2011

Discrete Stein characterizations and discrete information distances

Christophe Ley, Yvik Swan

We construct two different Stein characterizations of discrete distributions and use these to provide a natural connection between Stein characterizations for discrete distribution…

math.PR2011

A note on the normal approximation error for randomly weighted self-normalized sums

Siegfried Hoermann, Yvik Swan

Let $\bX=\{X_n\}_{n\geq 1}$ and $\bY=\{Y_n\}_{n\geq 1}$ be two independent random sequences. We obtain rates of convergence to the normal law of randomly weighted self-normalized s…

math.PR2017

Stein characterizations for linear combinations of gamma random variables

Benjamin Arras, Ehsan Azmoodeh, Guillaume Poly +1

In this paper we propose a new, simple and explicit mechanism allowing to derive Stein operators for random variables whose characteristic function satisfies a simple ODE. We apply…

math.PR2013

Local Pinsker inequalities via Stein's discrete density approach

Christophe Ley, Yvik Swan

Pinsker's inequality states that the relative entropy between two random variables and dominates the square of the total variation distance $d_{\mat…

math.PR2015

Distances between nested densities and a measure of the impact of the prior in Bayesian statistics

Christophe Ley, Gesine Reinert, Yvik Swan

In this paper we propose tight upper and lower bounds for the Wasserstein distance between any two {univariate continuous distributions} with probability densities and

math.ST2024

Stein's method of moments for truncated multivariate distributions

Adrian Fischer, Robert E. Gaunt, Yvik Swan

We use Stein characterisations to derive new moment-type estimators for the parameters of several truncated multivariate distributions in the i.i.d. case; we also derive the asympt…

math.PR2016

One step futher: an explicit solution to Robbins' problem when

Rémi Dendievel, Yvik Swan

Fix some and let be independent random variables drawn from the uniform distribution on . A decision maker is shown the variables se…

math.ST2024

Stein's Method of Moments on the Sphere

Adrian Fischer, Robert E. Gaunt, Yvik Swan

We use Stein characterizations to obtain new moment-type estimators for the parameters of three classical spherical distributions (namely the Fisher-Bingham, the von Mises-Fisher,…

math.PR2016

IT formulae for gamma target: mutual information and relative entropy

Benjamin Arras, Yvik Swan

In this paper, we introduce new Stein identities for gamma target distribution as well as a new non-linear channel specifically designed for gamma inputs. From these two ingredient…

math.PR2019

First order covariance inequalities via Stein's method

Marie Ernst, Gesine Reinert, Yvik Swan

We propose probabilistic representations for inverse Stein operators (i.e. solutions to Stein equations) under general conditions; in particular we deduce new simple expressions fo…

math.ST2014

Maximum likelihood characterization of distributions

Mitia Duerinckx, Christophe Ley, Yvik Swan

A famous characterization theorem due to C.F. Gauss states that the maximum likelihood estimator (MLE) of the parameter in a location family is the sample mean for all samples of a…

math.PR2016

Stein's method, many interacting worlds and quantum mechanics

Ian W. McKeague, Erol A. Peköz, Yvik Swan

Hall, Deckert and Wiseman (2014) recently proposed that quantum theory can be understood as the continuum limit of a deterministic theory in which there is a large, but finite, num…

math.PR2018

Regularity of solutions of the Stein equation and rates in the multivariate central limit theorem

Thomas Gallouët, Guillaume Mijoule, Yvik Swan

Consider the multivariate Stein equation , where is a standard -dimensional Gaussian random vector, and let be the solution giv…

math.PR2019

Distances between distributions via Stein's method

Marie Ernst, Yvik Swan

We build on the formalism developed in [arXiv:1906.08372v1] to propose new representations of solutions to Stein equations. We provide new uniform and non uniform bounds on these s…

math.PR2019

Simple variance bounds with applications to Bayesian posteriors and intractable distributions

Fraser Daly, Fatemeh Ghaderinezhad, Christophe Ley +1

Using coupling techniques based on Stein's method for probability approximation, we revisit classical variance bounding inequalities of Chernoff, Cacoullos, Chen and Klaassen. Taki…

math.PR2018

Stein-type covariance identities: Klaassen, Papathanasiou and Olkin-Shepp type bounds for arbitrary target distributions

Marie Ernst, Gesine Reinert, Yvik Swan

In this paper, we present a minimal formalism for Stein operators which leads to different probabilistic representations of solutions to Stein equations. These in turn provide a wi…

math.ST2011

A remark on the ARE between Wilcoxon's and van~der~Waerden's scores

Nadir Maaroufi, Camille Sabbah, Yvik Swan +1

This paper is concerned with a comparison of van der Waerden's and Wilcoxon's scores.

math.PR2010

A Stochastic Analysis of some Two-Person Sports

Davy Paindaveine, Yvik Swan

We consider two-person sports where each rally is initiated by a \emph{server}, the other player (the \emph{receiver}) becoming the server when he/she wins a rally. Historically, t…

stat.ME2023

Independent additive weighted bias distributions and associated goodness-of-fit tests

Bruno Ebner, Yvik Swan

We use a Stein identity to define a new class of parametric distributions which we call ``independent additive weighted bias distributions.'' We investigate related -type disc…

math.PR2011

A unified approach to Stein characterizations

Christophe Ley, Yvik Swan

This article deals with Stein characterizations of probability distributions. We provide a general framework for interpreting these in terms of the parameters of the underlying dis…

math.ST2025

Normal approximation for the posterior in exponential families

Adrian Fischer, Robert E. Gaunt, Gesine Reinert +1

In this paper, we obtain quantitative, non-asymptotic, and data-dependent \textit{Bernstein-von Mises type} bounds on the normal approximation of the posterior distribution in expo…

math.PR2025

Stein's method for Fréchet approximation: a regularly varying functions approach

Paul Mansanarez, Guillaume Poly, Yvik Swan

We develop a variant of Stein's method of comparison of generators to bound the Kolmogorov, total variation, and Wasserstein-1 distances between distributions on the real line. Our…

math.PR2023

Stein's density method for multivariate continuous distributions

Guillaume Mijoule, Martin Raič, Gesine Reinert +1

This paper provides a general framework for Stein's density method for multivariate continuous distributions. The approach associates to any probability density function a canonica…

math.PR2019

On infinite covariance expansions

Marie Ernst, Gesine Reinert, Yvik Swan

In this paper we provide a probabilistic representation of Lagrange's identity which we use to obtain Papathanasiou-type variance expansions of arbitrary order. Our expansions lead…

stat.AP2011

A Stochastic Analysis of Table Tennis

Yves Dominicy, Christophe Ley, Yvik Swan

We establish a general formula for the distribution of the score in table tennis. We use this formula to derive the probability distribution (and hence the expectation and variance…

stat.ME2022

Stein's Method Meets Computational Statistics: A Review of Some Recent Developments

Andreas Anastasiou, Alessandro Barp, François-Xavier Briol +11

Stein's method compares probability distributions through the study of a class of linear operators called Stein operators. While mainly studied in probability and used to underpin…