Statistical inference for Sobol pick freeze Monte Carlo method

Abstract : Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variability of a quantity of interest (output of the model). One of the statistical tools used to quantify the influence of each input variable on the output is the Sobol sensitivity index. We consider the statistical estimation of this index from a finite sample of model outputs. We study asymptotic and non-asymptotic properties of two estimators of Sobol indices. These properties are applied to significance tests and estimation by confidence intervals.
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Article dans une revue
Statistics, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2016, 50 (4), pp.881-902
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Soumis le : mardi 26 mars 2013 - 10:01:27
Dernière modification le : mardi 29 novembre 2016 - 21:06:23
Document(s) archivé(s) le : jeudi 27 juin 2013 - 03:59:53

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  • HAL Id : hal-00804668, version 1
  • ARXIV : 1303.6447

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Fabrice Gamboa, Alexandre Janon, Thierry Klein, Agnes Lagnoux-Renaudie, Clémentine Prieur. Statistical inference for Sobol pick freeze Monte Carlo method. Statistics, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2016, 50 (4), pp.881-902. <hal-00804668>

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