Estimation des densités: risque minimax

@article{Bretagnolle1978EstimationDD,  title={Estimation des densit{\'e}s: risque minimax},  author={J. L. Bretagnolle and Catherine Huber},  journal={Zeitschrift f{\"u}r Wahrscheinlichkeitstheorie und Verwandte Gebiete},  year={1978},  volume={47},  pages={119-137},  url={https://api.semanticscholar.org/CorpusID:122597694}}
  • J. BretagnolleC. Huber
  • Published1978
  • Mathematics
  • Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete
© Springer-Verlag, Berlin Heidelberg New York, 1978, tous droits réservés. L’accès aux archives du séminaire de probabilités (Strasbourg) (http://portail. mathdoc.fr/SemProba/) implique l’accord avec les conditions générales d’utilisation (http://www.numdam.org/legal.php). Toute utilisation commerciale ou impression systématique est constitutive d’une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright. 

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17 References

On Some Global Measures of the Deviations of Density Function Estimates

We consider density estimates of the usual type generated by a weight function. Limt theorems are obtained for the maximum of the normalized deviation of the estimate from its expected value, and for

Lower Bounds for Nonparametric Density Estimation Rates

In Wegman's paper [5] on nonparametric density estimation, he states that it would be interesting to show that there is no density estimator which has mean integrated square rate better than O(n-1).

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We consider the problem of sequential estimation of a density function f at a point x0 which may be known or unknown. Let Tn be a sequence of estimators of x0. For two classes of density estimators

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In brief, by "rate of convergence" we will mean the rate which an tends to zero. For a continuum of different choices of the set C specified by various Lipschitz conditions on the kth partial

On Estimation of a Probability Density Function and Mode

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