A Comparative Review of Sensitivity and Uncertainty Analysis of Large-Scale Systems—II: Statistical Methods
By D. Cacuci, M. Ionescu-Bujor. 2004
200 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/449d551bb1aab067088c2df4eb9f7c2c6b0d8f1e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
- Jessica Cariboni
- Andrea Saltelli
- Francesca Campolongo
- Jon C. Helton
- T. Trucano
- Laura Painton Swiler
- Jay D. Johnson
- Cédric J. Sallaberry
In Statistics and Probability
- Francesca Campolongo
- Andrea Saltelli
- Jessica Cariboni
- William Oberkampf
- Laura Painton Swiler
- Jon C. Helton
- Cédric J. Sallaberry
- C. Storlie
Citations in the corpus
- An effective screening design for sensitivity analysis of large models (2007, background): “Different approaches can be followed to test the sensitivity of a model (Saltelli et al., 2004, 2005; Cacuci and Ionesco-Bujor, 2004).”
- Survey of sampling-based methods for uncertainty and sensitivity analysis (2006, methodology): “(6-66) are replaced by the corresponding Savage scores ss(Oij), where”
- A methodology for performing global uncertainty and sensitivity analysis in systems biology. (2008, background): “See Iman and Helton, (1988) and Saltelli et al. (2000) for details on each of these approaches and Cacuci and Ionescu-Bujor (2004), Draper (1995), Helton (1993) and Saltelli et al. (2005) for more general reviews on US analysis.”
- Calibration, validation, and sensitivity analysis: What's what (2006, result): “This has been the subject of many previous presentations, for example [69–81].”