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This paper study sparse classification problems. We show that under single-index models, vanilla Lasso could give good estimate of unknown parameters. With this result, we see that even if the model i...
Stochastic simulators such as Monte-Carlo estimators are widely used in science and engineering to study physical systems through their probabilistic representation. Global sensitivity analysis aims t...
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
This work develops the asymptotic properties (weak consistency and Gaussianity), in the high-frequency limit, of approximate maximum likelihood estimators for the spectral parameters of Gaussian and i...
The ability to quantitatively assess the health of an ecosystem is often of great interest to those tasked with monitoring and conserving ecosystems. For decades, research in this area has relied upon...
We introduce the General Poverty Index (GPI),which summarizes most of the known and available poverty indices, in the form GPI=δ(A(Qn,n,Z)nB(Q,n)Qn Xj=1 w(µ1n+µ2Qn−µ3j+µ4...
We investigate the joint asymptotic behavior of so-called blocks estimator of the extremal index, that determines the mean length of clusters of extremes, based on the exceedances over different thres...
In data sets with many more features than observations, independent screening based on all univariate regression models leads to a computationally convenient variable selection method. Recent effort...
We show that under a linearity condition on the distribution of the predictors, the coefficient vector in a single-index regression can be estimated with the same efficiency as in the case when the ...
The suggested ordering of estimators uses the separation measure between the population with true and estimated values of parameter. It allows us ta choose one estimator as better in the cases wher...
We want to recover the regression function in the single-index model. Using an aggregation algorithm with local polynomial estimators, we answer in particular to the second part of Question 2 from Sto...
We derive the distribution of the center of mass S of the integrated superBrownian excursion (ISE) from the asymptotic distribution of the Wiener index for simple trees. Equivalently, this is the dist...
We give upper bounds for the probability $P(|f(X)-Ef(X)|>x)$, where $X$ is a stable random variable with index close to 2 and $f$ is a Lipschitz function. While the optimal upper bound is known to be ...
We give upper bounds for the probability $P(|f(X)-Ef(X)|>x)$, where $X$ is a stable random variable with index close to 2 and $f$ is a Lipschitz function. While the optimal upper bound is known to be ...

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