Paper Info
Title
Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models
Abstract
Many dynamic models are used for risk assessment and decision support in ecology and crop science. Such models generate time-dependent model predictions, with time either discretised or continuous. Their global sensitivity analysis is usually applied separately on each time output, but Campbell et al. (2006 [1]) advocated global sensitivity analyses on the expansion of the dynamics in a well-chosen functional basis. This paper focuses on the particular case when principal components analysis is combined with analysis of variance. In addition to the indices associated with the principal components, generalised sensitivity indices are proposed to synthesize the influence of each parameter on the whole time series output. Index definitions are given when the uncertainty on the input factors is either discrete or continuous and when the dynamic model is either discrete or functional. A general estimation algorithm is proposed, based on classical methods of global sensitivity analysis.
Year
DOI
Venue
2011
10.1016/j.ress.2010.12.002
Reliability Engineering & System Safety
Keywords
DocType
Volume
Dynamic model,Factorial design,Latin hypercube sampling,Principal components analysis,RKHS,Sensitivity analysis,Sobol' decomposition
Journal
96
Issue
ISSN
Citations 
4
0951-8320
20
PageRank 
References 
Authors
1.13
4
3
Name
Order
Citations
PageRank
Matieyendou Lamboni1201.47
Hervé Monod2394.36
David Makowski3201.13