Adaptive optimal kernel density estimation for directional data

Thanh Mai Pham Ngoc

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arXiv · 1808.02361

Adaptive optimal kernel density estimation for directional data

Thanh Mai Pham Ngoc

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Abstract

We focus on the nonparametric density estimation problem with directional data. We propose a new rule for bandwidth selection for kernel density estimation. Our procedure is automatic, fully data-driven and adaptive to the smoothness degree of the density. We obtain an oracle inequality and optimal rates of convergence for the L2 error. Our theoretical results are illustrated with simulations.

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Thanh Mai Pham Ngoc. 2018-08-07. Adaptive optimal kernel density estimation for directional data. https://arxiv.org/abs/1808.02361

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