Abstract
We provide new general kernel selection rules thanks to penalized least-squares criteria. We derive optimal oracle inequalities using adequate concentration tools. We also investigate the problem of minimal penalty as described in Birgé and Massart (2007, Probab. Theory Relat. Fields, 138(1–2):33–73).
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APA
Lerasle, M., Magalhães, N. M., & Reynaud-Bouret, P. (2016). Optimal Kernel Selection for Density Estimation. In Progress in Probability (Vol. 71, pp. 425–460). Birkhauser. https://doi.org/10.1007/978-3-319-40519-3_19
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