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We prove a central limit theorem for linear triangular arrays under weak dependence conditions. Our result is then applied to the study of dependent random variables sampled by a Z-valued transient random walk. This extends the results obtained by Guillotin-Plantard & Schneider (2003). An application to parametric estimation by random sampling is also(More)
This paper deals with the random balance design method (RBD) and its hybrid approach, RBD-FAST. Both these global sensitivity analysis methods originate from Fourier amplitude sensitivity test (FAST) and are consequently faced with the main problems inherent to discrete harmonic analysis. As some authors pointed out in these methods, certain estimates of(More)
We present a reduced basis offline/online procedure for viscous Burgers initial boundary value problem, enabling efficient approximate computation of the solutions of this equation for parametrized viscosity and initial and boundary value data. This procedure comes with a fast-evaluated rigorous error bound certifying the approximation procedure. Our(More)
This paper deals with the problem of estimating the level sets L(c) = {F (x) ≥ c}, with c ∈ (0, 1), of an unknown distribution function F on R 2 +. A plug-in approach is followed. That is, given a consistent estimator Fn of F , we estimate L(c) by Ln(c) = {Fn(x) ≥ c}. In our setting, non-compactness property is a priori required for the level sets to(More)
Global sensitivity analysis is often impracticable for complex and resource intensive numerical models, as it requires a large number of runs. The metamodel approach replaces the original model by an approximated code that is much faster to run. This paper deals with the information loss in the estimation of sensitivity indices due to the metamodel(More)
Let S = (S k) k≥0 be a random walk on Z and ξ = (ξ i) i∈Z a stationary random sequence of centered random variables, independent of S. We consider a random walk in random scenery that is the sequence of random variables (Σ n) n≥0 where Σ n = n k=0 ξ S k , n ∈ N. Under a weak dependence assumption on the scenery ξ we prove a functional limit theorem(More)
We prove a version for random measures of the celebrated Kantorovich-Rubinštein duality theorem and we give an application to the coupling of random variables which extends and unifies known results. Résumé Nous démontrons une version du théorème de dualité de Kantorovich-Rubinštein pour les mesures aléatoires, et nous donnons une application au couplage(More)
We propose an estimation procedure for linear functionals based on Gaussian model selection techniques. We show that the procedure is adaptive, and we give a non asymptotic oracle inequality for the risk of the selected estimator with respect to the Lp loss. An application to the problem of estimating a signal or its r th derivative at a given point is(More)