Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/36617 
Authors: 
Year of Publication: 
2008
Series/Report no.: 
Technical Report No. 2008,08
Publisher: 
Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Abstract: 
In this paper, a method for estimating monotone, convex and log-concave densities is proposed. The estimation procedure consists of an unconstrained kernel estimator which is modi?ed in a second step with respect to the desired shape constraint by using monotone rearrangements. It is shown that the resulting estimate is a density itself and shares the asymptotic properties of the unconstrained estimate. A short simulation study shows the ?nite sample behavior.
Subjects: 
Convexity
log-concavity
monotone rearrangements
monotonicity
nonparametric density estimation
Document Type: 
Working Paper

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