Concept

Statistique d'ordre

Publications associées (41)

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Frédéric Courbin, Gianluca Castignani, Jean-Luc Starck, Austin Chandler Peel, Maurizio Martinelli, Yi Wang, Richard Massey, Fabio Finelli, Marcello Farina

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale ...

EDP SCIENCES S A2023

Peak Value-at-Risk Estimation for Stochastic Differential Equations using Occupation Measures

Matteo Raphael Tacchi

This paper proposes an algorithm to upper-bound maximal quantile statistics of a state function over the course of a Stochastic Differential Equation (SDE) system execution. This chance-peak problem is posed as a nonconvex program aiming to maximize the Va ...

New York2023

Density Estimation In Rkhs With Application To Korobov Spaces In High Dimensions

Fabio Nobile, Yoshihito Kazashi

A kernel method for estimating a probability density function from an independent and identically distributed sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined b ...

SIAM PUBLICATIONS2023

Influence of advanced footwear technology on sub-2 hour marathon and other top running performances

Raphaël Gérard Théodore Michel Marie de Deloÿe et Fourcade de Fondeville

In 2019, Eliud Kipchoge ran a sub-two hour marathon wearing Nike's Alphafly shoes. Despite being the fastest marathon time ever recorded, it wasn't officially recognized as race conditions were tightly controlled to maximize his success. Besides, Kipchoge' ...

WALTER DE GRUYTER GMBH2022

Distributionally Robust Optimization with Polynomial Densities: Theory, Models and Algorithms

Daniel Kuhn

In distributionally robust optimization the probability distribution of the uncertain problem parameters is itself uncertain, and a fictitious adversary, e.g., nature, chooses the worst distribution from within a known ambiguity set. A common shortcoming o ...

2020

Quantifying the information impact of future searches for exoplanetary biosignatures

Claudio Grimaldi

One of the major goals for astronomy in the next decades is the remote search for biosignatures (i.e., the spectroscopic evidence of biological activity) in exoplanets. Here we adopt a Bayesian statistical framework to discuss the implications of such futu ...

NATL ACAD SCIENCES2020

Fully automated detection, segmentation, and analysis of in vivo RPE single cells

Christophe Moser, Timothé Laforest, Laura Emmanuelle Kowalczuk, Florentino Luciano Caetano Dos Santos

Objective To develop a fully automated method of retinal pigmented epithelium (RPE) cells detection, segmentation and analysis based on in vivo cellular resolution images obtained with the transscleral optical phase imaging method (TOPI). Methods Fourteen ...

NATURE PUBLISHING GROUP2020

A nonparametric method for producing isolines of bivariate exceedance probabilities

Emeric Rolland Georges Thibaud

We present a method for drawing isolines indicating regions of equal joint exceedance probability for bivariate data. The method relies on bivariate regular variation, a dependence framework widely used for extremes. The method we utilize for characterizin ...

SPRINGER2019

Reconstructing the Drizzle Mode of the Raindrop Size Distribution Using Double-Moment Normalization

Alexis Berne, Timothy Hugh Raupach

Commonly used disdrometers tend not to accurately measure concentrations of very small drops in the raindrop size distribution (DSD), either through truncation of the DSD at the small-drop end or because of large uncertainties on these measurements. Recent ...

AMER METEOROLOGICAL SOC2019

Meandering particle bunches and a link between averages of time series of particle counts and higher-order moments

Ambrogio Fasoli, Ivo Furno, Paolo Ricci, Marcelo Baquero Ruiz, Fabian Manke

Time-averaged spatially resolved measurements are used in many fields of physics to determine spatial distributions of a physical quantity. Although one could think that time averaging suppresses all information on time variation, there are some situations ...

2018

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