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2 results

  • Risk bounds for new M-estimation problems∗

  • Nabil Rachdi, Jean-Claude Fort, Thierry Klein
  • Journal:
    ESAIM: Probability and Statistics / Volume 17 / 2013
    Published online by Cambridge University Press:
    04 November 2013, pp. 740-766
    Print publication:
    2013

  • In this paper, we consider a new framework where two types of data are available:experimental dataY1,...,Ynsupposed to be i.i.d from Y and outputs from a simulated reduced model.We develop a procedure for parameter estimation to characterize a feature of thephenomenon Y. We prove a risk bound qualifying the proposed procedure interms of the number of experimental data n, reduced model complexity andcomputing budget m. The method we present is general enough to cover awide range of applications. To illustrate our procedure we provide a numericalexample.