Shape constrained kernel density estimation

Melanie Birke

No 2008,08, Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen

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.

Keywords: Convexity; log-concavity; monotone rearrangements; monotonicity; nonparametric density estimation (search for similar items in EconPapers)
Date: 2008
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