Robust nonparametric estimators of monotone boundaries

By Abdelaati Daouia, Léopold Simar. 2005

54 citations recorded by the source corpus.

This paper revisits some asymptotic properties of the robust nonparametric estimators of order-m and order-@a quantile frontiers and proposes isotonized version of these estimators. Previous convergence properties of the order-m frontier are extended (from weak uniform convergence to complete uniform convergence). Complete uniform convergence of the order-m (and of the quantile order-@a) nonparametric estimators to the boundary is also established, for an appropriate choice of m (and of @a, respectively) as a function of the sample size. The new isotonized estimators share the asymptotic properties of the original ones and a simulated example shows, as expected, that these new versions are even more robust than the original estimators. The procedure is also illustrated through a real data set.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9018682b81eba99de100238276d6bae8563ed302

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Estimation and Inference in Nonparametric Frontier Models: Recent Developments and Perspectives (2013, methodology): “Simar and Vanhems (2012) extended the ideas of Daouia and Simar (2007) and Wheelock and Wilson (2008) to develop a directional orderα measure of efficiency.”