This 'block thresholding' approach does indeed improve performance, by allowing greater adaptivity and reducing mean squared error.
The purpose of the present paper is to explore numerical properties of the latter procedure, which we call `block thresholding', and to compare it with termby- ...
On the block thresholding wavelet estimators with censored data
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We consider block thresholding wavelet-based density estimators with randomly right-censored data and investigate their asymptotic convergence rates.
Abstract: In this article we investigate the asymptotic and numerical properties of a class of block thresholding estimators for wavelet regression.
Dec 13, 2004 · Remark 3.2 Cai (2002) investigate the asymptotic and numerical properties of a class of block thresholding estimators for wavelet regression.
We conclude with a numerical study which compares the finite-sample performance among block thresholding estimators as well as with other wavelet methods.
Numerical performance of block thresholded wavelet estimators. Free Keywords ... Good for learning multi-resolution approximation/analysis and wavelet transform.
We also report a comprehensive suite of numerical simulations to support our theoretical findings. The practical performance of our block estimator compares ...
In this article, we show that block-thresholded wavelet estimators still attain minimax convergence rates when the mean functions belong to a wide range of ...
Numerical results show that it has superior finite sample performance in comparison to the other leading wavelet thresholding estimators. Keywords adaptivity, ...