Statistical Science

Sensitivity Anaysis as an Ingredient of Modeling

F. Campolongo, A. Saltelli, and S. Tarantola

Full-text: Open access

Abstract

We explore the tasks where sensitivity analysis (SA) can be useful and try to assess the relevance of SA within the modeling process. We suggest that SA could considerably assist in the use of models, by providing objective criteria of judgement for different phases of the model­building process: model identification and discrimination; model calibration; model corroboration.

We review some new global quantitative SA methods and suggest that these might enlarge the scope for sensitivity analysis in computational and statistical modeling practice. Among the advantages of the new methods are their robustness, model independence and computational convenience.

The discussion is based on worked examples.

Article information

Source
Statist. Sci. Volume 15, Number 4 (2000), 377-395.

Dates
First available in Project Euclid: 24 December 2001

Permanent link to this document
http://projecteuclid.org/euclid.ss/1009213004

Digital Object Identifier
doi:10.1214/ss/1009213004

Mathematical Reviews number (MathSciNet)
MR1847774

Citation

Saltelli, A.; Tarantola, S.; Campolongo, F. Sensitivity Anaysis as an Ingredient of Modeling. Statistical Science 15 (2000), no. 4, 377--395. doi:10.1214/ss/1009213004. http://projecteuclid.org/euclid.ss/1009213004.


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