Wavelet Methods in Nonparametric Regression Based on Experimental Data

摘要

In this paper we will present wavelet thresholding estimators in nonparametric regression for denoising data modelled as observations of a signal contaminated with additive Gaussian noise. We compare performance of the minimax thresholding rule with VisuShrink thresholding rule in the context of the mean-squared error.