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arXiv · 1111.2807

Spatially Adaptive Density Estimation by Localised Haar Projections

Florian Gach·Richard Nickl·Vladimir Spokoiny
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Abstract

Given a random sample from some unknown density $f_0: \mathbb R \to [0, \infty)$ we devise Haar wavelet estimators for $f_0$ with variable resolution levels constructed from localised test procedures (as in Lepski, Mammen, and Spokoiny (1997, Ann. Statist.)). We show that these estimators adapt to spatially heterogeneous smoothness of $f_0$, simultaneously for every point $x$ in a fixed interval, in sup-norm loss. The thresholding constants involved in the test procedures can be chosen in practice under the idealised assumption that the true density is locally constant in a neighborhood of the point $x$ of estimation, and an information theoretic justification of this practice is given.

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Florian Gach, Richard Nickl, Vladimir Spokoiny. 2011-11-11. Spatially Adaptive Density Estimation by Localised Haar Projections. https://arxiv.org/abs/1111.2807

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