Kernel adjusted density estimation

Ramidha Srihera (1) , Winfried Stute (2)

1 Faculty of Science and Technology
2 JLU - Justus-Liebig-Universität Gießen = Justus Liebig University

We propose and study a kernel estimator of a density in which the kernel is adapted to the data but not fixed. The smoothing procedure is followed by a location-scale transformation to reduce bias and variance. The new method naturally leads to an adaptive choice of the smoothing parameters which avoids asymptotic expansions.

Mots clés: Kernel density estimator; Adaptive choice

Domaines: Bio-informatique [q-bio.QM]; Bio-Informatique, Biologie Systémique [q-bio.QM]

Ramidha Srihera, Winfried Stute. Kernel adjusted density estimation. Statistics and Probability Letters, 2011, 81 (5), pp.571. ⟨10.1016/j.spl.2011.01.013⟩. ⟨hal-00725101⟩