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Risk bounds for new M-estimation problems

Nabil RachdiJean-Claude FortThierry Klein — 2013

ESAIM: Probability and Statistics

In this paper, we consider a new framework where two types of data are available: experimental data supposed to be i.i.d from and outputs from a simulated reduced model. We develop a procedure for parameter estimation to characterize a feature of the phenomenon . We prove a risk bound qualifying the proposed procedure in terms of the number of experimental data , reduced model complexity and computing...

Stochastic Inverse Problem with Noisy Simulator. Application to aeronautical model

Nabil RachdiJean-Claude FortThierry Klein — 2012

Annales de la faculté des sciences de Toulouse Mathématiques

Inverse problem is a current practice in engineering where the goal is to identify parameters from observed data through numerical models. These numerical models, also called Simulators, are built to represent the phenomenon making possible the inference. However, such representation can include some part of variability or commonly called uncertainty (see [4]), arising from some variables of the model. The phenomenon we study is the fuel mass needed...

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