@techreport{Simar2003Improve,
abstract = {In frontier analysis, most of the nonparametric approaches (DEA, FDH) are
based on envelopment ideas which suppose that with probability one, all the
observed units belong to the attainable set. In these "deterministic" frontier
models, statistical theory is now mostly available. In the presence of noise,
this is no more true and envelopment estimators could behave dramatically
since they are very sensitive to extreme observations that could result only
from noise. DEA/FDH techniques would provide estimators with an error of
the order of the standard deviation of the noise. In this paper we propose
to adapt some recent results on detecting change points, to improve the
performances of the classical DEA/FDH estimators in the presence of noise.
We show by simulated examples that the procedure works well when the
noise is of moderate size, in term of noise to signal ratio. It turns out that
the procedure is also robust to outliers.},
author = {L\'{e}opold Simar},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {330; Nonparametric frontier; Stochastic DEA/FDH; Robustness to outliers; Nichtparametrisches Verfahren; Data-Envelopment-Analyse; Sch\"{a}tztheorie; Theorie},
language = {eng},
note = {urn:nbn:de:kobv:11-10050382},
number = {2003,33},
title = {How to Improve the Performances of DEA/FDH Estimators in the Presence of Noise?},
type = {Discussion papers of interdisciplinary research project 373},
url = {http://hdl.handle.net/10419/22248},
year = {2003}
}