Birke, Melanie2008-11-262008-11-262008-11-26http://hdl.handle.net/2003/2587110.17877/DE290R-14453In 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 modified 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 finite sample behavior.enConvexityLog-concavityMonotone rearrangementMonotonicityNonparametric density estimation004report