Abstract
SUMMARY Methods based on design transformation and equal-number binning are shown to overcome problems of design sparseness, while retaining excellent theoretical properties. In company with local linear smoothing they produce optimal estimators, although with optimality defined a little differently from in the nontransformed case. When used in conjunction with wavelet techniques they overcome problems of stochastic design, but, unlike related techniques based on convolution and interpolation, do not degrade features of the signal through prior smoothing, or inflate the variance.
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