Bardet, Jean-Marc Guenaizi, Abdellatif

This paper is devoted to the offline multiple changes detection for long memory processes. The observations are supposed to satisfy a semi-parametric long memory assumption with distinct memory parameters on each stage. A penalized local Whittle contrast is considered for estimating all the parameters. The consistency as well as convergence rates a...

Daouia, Abdelaati Girard, Stephane Stupfler, Gilles

Expectiles define a least squares analogue of quantiles. They are determined by tail expectations rather than tail probabilities. For this reason and many other theoretical and practical merits, expec-tiles have recently received a lot of attention, especially in actuarial and financial risk management. Their estimation, however, typically requires...

Castellan, Gwenaëlle Cousien, Anthony Tran, Viet Chi

The global sensitivity analysis is a set of methods aiming at quantifying the contribution of an uncertain input parameter of the model (or combination of parameters) on the variability of the response. We consider here the estimation of the Sobol indices of order 1 which are commonly-used indicators based on a decomposition of the output's varianc...

Benammar, Meryem Piantanida, Pablo Shamai, Shlomo

This work investigates the general two-user Compound Broadcast Channel (BC) where an encoder wishes to transmit common and private messages to two receivers while being oblivious to two possible channel realizations controlling the communication. The focus is on the characterization of the largest achievable rate region by resorting to more evolved...

Aaron, Catherine Cholaquidis, Alejandro

Given a sample of a random variable supported by a smooth compact manifold M ⊂ R d , we propose a test to decide whether the boundary of M is empty or not with no preliminary support estimation. The test statistic is based on the maximal distance between a sample point and the average of its k n −nearest neighbors. We prove that the level of the te...

Albert, Clément Dutfoy, Anne Gardes, Laurent Girard, Stéphane

We propose a new estimator for extreme quantiles under the log-generalized Weibull-tail model, introduced by Cees de Valk. This model relies on a new regular variation condition which, in some situations, permits to extrapolate further into the tails than the classical assumption in extreme-value theory. The asymptotic normality of the estimator is...

Da Veiga, Sébastien Marrel, Amandine

The analysis of expensive numerical simulators usually requires metamodelling techniques, among which Gaussian process regression is one of the most popular approaches. Frequently, the code outputs correspond to physical quantities with a behavior which is known a priori: chemical concentrations lie between 0 and 1, the output is increasing with re...

Ahmed, Manaf Maume-Deschamps, Véronique Ribereau, Pierre Vial, Céline

In this paper, we consider isotropic and stationary max-stable, inverse max-stable and max-mixture processes $X=(X(s))_{s\in\bR^2}$ and the damage function $\cD_X^{\nu}= |X|^\nu$ with $0

Abu-Awwad, Abdul-Fattah Maume-Deschamps, Véronique Pierre, Ribereau

Max-mixture processes are defined as Z = max(aX, (1 − a)Y) with X an asymptotic dependent (AD) process, Y an asymptotic independent (AI) process and a ∈ [0, 1]. So that, the mixing coefficient a may reveal the strength of the AD part present in the max-mixture process. In this paper we focus on two tests based on censored pairwise likelihood estima...

Huet, Sylvie Taupin, Marie-Luce

We propose to estimate a metamodel and the sensitivity indices of a complex model m in the Gaussian regression framework. Our approach combines methods for sensitivity analysis of complex models and statistical tools for sparse non-parametric estimation in multivariate Gaussian regression model. It rests on the construction of a metamodel for aprox...