Entropic kernels for data smoothing

Data smoothing or regression kernels based on locational entropy embody the principle that observations towards the extremes of the chosen data window should provide less information than those at the midpoint. Weight patterns can be flexible, depending on the choice of prior information density.

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Year of publication:	2013
Authors:	Bowden, Roger
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 83.2013, 3, p. 916-922
Publisher:	Elsevier
Subject:	Bandwidth \| Data smoothing \| Kernel regression \| Locational entropy \| Subjective probabilities

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010616883