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On pointwise adaptive curve estimation based on inhomogeneous data

Stéphane Gaïffas — 2007

ESAIM: Probability and Statistics

We want to recover a signal based on noisy inhomogeneous data (the amount of data can vary strongly on the estimation domain). We model the data using nonparametric regression with random design, and we focus on the estimation of the regression at a fixed point with little, or much data. We propose a method which adapts both to the local amount of data (the design density is unknown) and to the local smoothness of the regression function. The procedure consists of a local...

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