Estimation of the density of a determinantal process
Yannick Baraud (2013)
Confluentes Mathematici
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We consider the problem of estimating the density of a determinantal process from the observation of independent copies of it. We use an aggregation procedure based on robust testing to build our estimator. We establish non-asymptotic risk bounds with respect to the Hellinger loss and deduce, when goes to infinity, uniform rates of convergence over classes of densities of interest.