Reliability of global sensitivity indices

References

• Saltelli , A. , Tarantola , S. and Campolongo , F. 2000 . Sensitivity analysis as an ingredient of modeling . Statist. Sci. , 15 : 377 – 395 .
   Web of Science ®Google Scholar
• Saltelli , A. , Ratto , M. , Tarantola , S. and Campolongo , F. 2005 . Sensitivity analysis for chemical models . Chem. Rev. , 105 : 2811 – 2826 .
   PubMed Web of Science ®Google Scholar
• Saltelli , A. , Chan , K. and Scott , M. 2000 . Sensitivity Analysis , West Sussex : John Wiley and Sons .
   Google Scholar
• Saltelli , A. and Tarantola , S. 2002 . On the relative importance of input factors in mathematical models: Safety assessment for nuclear waste disposal . J. Am. Statist. Assoc. , 97 : 702 – 709 .
   Web of Science ®Google Scholar
• Cukier , R. I. , Schaibly , J. H. and Shuler , K. E. 1975 . Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. III. Analysis of the approximations . J. Chem. Phys. , 63 : 1140 – 1149 .
   Web of Science ®Google Scholar
• Cukier , R. I. , Levine , H. B. and Shuler , K. E. 1978 . Nonlinear sensitivity analysis of multiparameter model systems . J. Comput. Phys. , 26 : 1 – 42 .
   Web of Science ®Google Scholar
• Schaibly , J. H. and Shuler , K. E. 1973 . Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. II. Applications . J. Chem. Phys. , 59 : 3879 – 3888 .
   Web of Science ®Google Scholar
• Cukier , R. I. , Fortuin , C. M. , Shuler , K. E. , Petschek , A. G. and Schaibly , J. H. 1973 . Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I. Theory . J. Chem. Phys. , 59 : 3873 – 3878 .
   Web of Science ®Google Scholar
• Borgonovo , E. 2006 . Measuring uncertainty importance: Investigation and comparison of alternative approaches . Risk. Anal. , 26 : 1349 – 1361 .
   PubMed Web of Science ®Google Scholar
• Tarantola , S. , Gatelli , D. and Mara , T. A. 2006 . Random balance designs for the estimation of first order global sensitivity indices . Reliab. Eng. Syst. Safe. , 91 : 717 – 727 .
   Web of Science ®Google Scholar
• Xu , C. and Gertner , G. Z. 2011 . Understanding and comparisons of different sampling approaches for the Fourier amplitudes sensitivity test(FAST) . Comput. Stat. Data. Anal , 55 ( 1 ) : 184 – 198 .
   PubMed Web of Science ®Google Scholar
• Xu , C. and Gertner , G. Z. 2007 . Extending a global sensitivity analysis technique to models with correlated parameters . Comput. Stat. Data. Anal. , 51 : 5579 – 5590 .
   Google Scholar
• Xu , C. and Gertner , G. Z. 2008 . A general first-order global sensitivity analysis method . Reliab. Eng. Syst. Safe , 93 : 1060 – 1071 .
   Web of Science ®Google Scholar
• Saltelli , A. , Tarantola , S. and Chan , K. P.S. 1999 . A quantitative model-independent method for global sensitivity analysis of model output . Technometrics , 41 : 39 – 56 .
   Web of Science ®Google Scholar
• Scheller , R. and Mladenoff , D. 2007 . An ecological classification of forest landscape simulation models: Tools and strategies for understanding broad-scale forested ecosystems . Landsc. Ecol. , 22 : 491 – 505 .
   Google Scholar
• He , H. S. 2008 . Forest landscape models: Definitions, characterization, and classification . For. Ecol. Manag. , 254 : 484 – 498 .
   Web of Science ®Google Scholar
• Xu , C. , Gertner , G. Z. and Scheller , R. M. 2009 . Uncertainties in the response of a forest landscape to global climatic change . Glob. Chang. Biol. , 15 : 116 – 131 .
   Web of Science ®Google Scholar
• Reiter , P. 2007 . Oviposition, dispersal, and survival in Aedes aegypti: Implications for the efficacy of control strategies . Vector Borne Zoonotic Dis. , 7 : 261 – 274 .
   PubMedGoogle Scholar
• Otero , M. , Schweigmann , N. and Solari , H. G. 2008 . A stochastic spatial dynamical model for Aedes aegypti . Bull. Math. Biol. , 70 : 1297 – 1325 .
   PubMedGoogle Scholar
• Magori , K. , Legros , M. , Puente , M. E. , Focks , D. A. , Scott , T. W. , Lloyd , A. and Gould , F. 2009 . Skeeter Buster: A stochastic, spatially-explicit modeling tool for studying Aedes aegypti population replacement and population suppression strategies . PLoS. Negl. Trop. Dis. , 3 : e508
   PubMedGoogle Scholar
• Fang , S. F. , Gertner , G. Z. , Shinkareva , S. , Wang , G. X. and Anderson , A. 2003 . Improved generalized Fourier amplitude sensitivity test (FAST) for model assessment . Stat. Comput. , 13 : 221 – 226 .
   Google Scholar
• Lu , Y. and Mohanty , S. 2001 . Sensitivity analysis of a complex, proposed geologic waste disposal system using the Fourier amplitude sensitivity test method . Reliab. Eng. Syst. Safe , 72 : 275 – 291 .
   Web of Science ®Google Scholar
• Meadows , D. H. , Meadows , D. L. and Randers , J. 1992 . Beyond the Limits , Post Mills, Vermont : Chelsea Green Publishing .
   Google Scholar
• Iman , R. L. , Johnson , M. E. and Schroeder , T. A. 2002 . Assessing hurricane effects. Part 1. Sensitivity analysis . Reliab. Eng. Syst. Safe , 78 : 131 – 145 .
   Google Scholar
• Kanso , A. , Chebbo , G. and Tassin , B. 2006 . Application of MCMC-GSA model calibration method to urban runoff quality modeling . Reliab. Eng. Syst. Safe , 91 : 1398 – 1405 .
   Web of Science ®Google Scholar
• Iman , R. L. and Conover , W. J. 1982 . A distribution-free approach to inducing rank correlation among input variables . Commun. Stat. Simul. C , 11 : 311 – 334 .
   Web of Science ®Google Scholar
• Lehmann , E. L. 1999 . Elements of Large-sample Theory , New York : Springer .
   Google Scholar