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Adaptive Density Estimation Using Projection Kernels and Penalized Comparison to Overfitting
In this work, we study wavelet projection estimators for density estimation, based on compactly supported $\mathcal S$-regular scaling functions. The main issue is the choice of the resolution level, which determines the bias--variance trade-off. We select this level by a Penalized Comparison to Ove
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