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Nonparametric kernel regression subject to monotonicity constraints

Huang, Li-Shan; Hall, Peter


We suggest a method for monotonizing general kernel-type estimators, for example local linear estimators and Nadaraya .Watson estimators. Attributes of our approach include the fact that it produces smooth estimates, indeed with the same smoothness as the unconstrained estimate. The method is applicable to a particularly wide range of estimator types, it can be trivially modified to render an estimator strictly monotone and it can be employed after the smoothing step has been implemented....[Show more]

CollectionsANU Research Publications
Date published: 2001
Type: Journal article
Source: The Annals of Statistics
DOI: 10.1214/aos/1009210683
Access Rights: Open Access


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