On shape-preserving probabilistic wavelet approximators

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Abstract
We introduce a general class of shape-preserving wavelet approximating operators (approximators) which transform cumulative distribution functions and densities into functions of the same type. Our operators can be considered as a generalization of the operators introduced by Anastassiou and Yu [1]. Further, we extend the consideration by studying the approximation properties for the whole variety of Lp:-norms, 0
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Author(s)
Dechevsky, Lubomir
Penev, Spiridon
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Publication Year
1997
Resource Type
Journal Article
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UNSW Faculty