@article{ref1,
title="A nonparametric importance sampling estimator for moment independent importance measures",
journal="Reliability engineering and system safety",
year="2019",
author="Derennes, Pierre and Morio, Jérôme and Simatos, Florian",
volume="187",
number="",
pages="3-16",
abstract="Moment independent importance measures have been proposed by Borgonovo [1] in order to alleviate some of the drawbacks of variance-based sensibility indices. They have gained increasing attention over the last years but their estimation remains a challenging issue. An effective estimation scheme in the case of correlated inputs, referred to as single-loop method, has been proposed by Wei et al. [2]. In this paper we show via simulation that this method may be inaccurate, making for instance 40% error in the simplest possible Gaussian case. We then propose a new estimation scheme which greatly improves the accuracy of the single-loop method, up to a factor 10 in some simple numerical examples. We prove that our estimator is strongly consistent and several simulation results are presented to demonstrate the advantages of the proposed method.<p /> <p>Language: en</p>",
language="en",
issn="0951-8320",
doi="10.1016/j.ress.2018.02.009",
url="http://dx.doi.org/10.1016/j.ress.2018.02.009"
}