Large and moderate deviations principles for recursive kernel estimators of a multivariate density and its partial derivatives

نویسندگان

  • Abdelkader Mokkadem
  • Mariane Pelletier
  • Baba Thiam
چکیده

Abstract: In this paper we prove large and moderate deviations principles for the recursive kernel estimator of a probability density function and its partial derivatives. Unlike the density estimator, the derivatives estimators exhibit a quadratic behaviour not only for the moderate deviations scale but also for the large deviations one. We provide results both for the pointwise and the uniform deviations.

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تاریخ انتشار 2006