Sensitivity analysis: A review of recent advances
By Emanuele Borgonovo, Elmar Plischke. European Journal of Operational Research, 2016
1,059 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/a84863d13f1041d99090a4a4982e66b436d42455
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Jianfei Cai
- Haitao Liu
- Yew-Soon Ong
- Jack P. C. Kleijnen
- Jim W. Hall
- Francesca Pianosi
- Thorsten Wagener
- Keith Beven
In Statistics and Probability
- Thorsten Wagener
- Francesca Pianosi
- Yew-Soon Ong
- Jack P. C. Kleijnen
- Jianfei Cai
- Haitao Liu
- Jim W. Hall
- David B. Stephenson
Citations in the corpus
- SHAPLEY EFFECTS FOR SENSITIVITY ANALYSIS WITH CORRELATED INPUTS: COMPARISONS WITH SOBOL' INDICES, NUMERICAL ESTIMATION AND APPLICATIONS (2017, neutral): “When constructing and using numerical models simulating physical phenomena, global sensitivity analysis (SA) methods are valuable tools [1, 2, 3, 4].”
- A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design (2017, background): “The SA is a very broad topic and has been widely reviewed in different fields, see (Kleijnen 2005; Saltelli et al. 2008; Tian 2013; Janouchová and Kučerová 2013; Iooss and Lemaître 2015; Borgonovo and Plischke 2016).”
- Analysis of resilience strategies and ripple effect in blockchain-coordinated supply chains: An agent-based simulation study (2020, neutral): “There are different types of sensitivity analyses, depending on the target of the analysis (Borgonovo and Plischke, 2016).”
- Regression and Kriging metamodels with their experimental designs in simulation: A review (2017, methodology): “The estimation of the various sensitivity meaures may use LHS, and replace the simulation model by a Kriging etamodel; see Borgonovo and Plischke (2016) and Saltelli et al.”
- Sensitivity analysis of environmental models: A systematic review with practical workflow (2014, methodology): “…review in this regard are the introduction to sensitivity assessment of simulation models by Norton (2015), the literature reviews (with a focus on the chemical modelling literature) by Saltelli et al. (2005, 2012) and the review of recent methodological advances by Borgonovo and Plischke (2016).”