Global sensitivity analysis offers a set of tools tailored to the impact assessment of certain assumptions on a model¿s output. A recent book on the topic covers those issues. Given the limited space for discussing thoroughly any of those methods, we summarize in this paper the main conclusions that derive from the application of various global sensitivity analysis methods on chemical models, econometric studies, financial models and composite indicators.JRC.G.9-Econometrics and statistical support to antifrau
Sensitivity analysis assesses the influence of input parameters on the conclusion of a model. Tradit...
AbstractThe majority of published sensitivity analyses (SAs) are either local or one factor-at-a-tim...
Abstract Sensitivity analysis is an essential paradigm in Earth and Environmental Systems modeling. ...
This chapter makes a review, in a complete methodological framework, of various global sensitivity a...
In the field of modelling it is easier to find academic papers, guidelines tailored to specific disc...
Practices for global sensitivity analysis of model output are described in a recent textbook (Saltel...
A review of quantitative sensitivity analysis methods in ChemistyJRC.G.9-Econometrics and statistica...
As computing power increases and data relating to elementary chemical and physical processes improve...
Fourteen years after Science’s review of sensitivity analysis methods in 1989 (System analysis at mo...
We present two methods for the estimation of main effects in global sensitivity analysis. The method...
A new method for sensitivity analysis of model output is introduced. It is based on the Fourier Ampl...
Some recent articles, all in volume 102 of JGR, Atmosphere, use sensitivity analysis (SA) for mechan...
We present computational tools to analyse some key properties of DSGE models and address the followi...
Climate policy decisions rely heavily on the predictions of climate–economic models. These models ar...
Motivated by an application in the realm of climate change economics,we develop and prove the mathem...
Sensitivity analysis assesses the influence of input parameters on the conclusion of a model. Tradit...
AbstractThe majority of published sensitivity analyses (SAs) are either local or one factor-at-a-tim...
Abstract Sensitivity analysis is an essential paradigm in Earth and Environmental Systems modeling. ...
This chapter makes a review, in a complete methodological framework, of various global sensitivity a...
In the field of modelling it is easier to find academic papers, guidelines tailored to specific disc...
Practices for global sensitivity analysis of model output are described in a recent textbook (Saltel...
A review of quantitative sensitivity analysis methods in ChemistyJRC.G.9-Econometrics and statistica...
As computing power increases and data relating to elementary chemical and physical processes improve...
Fourteen years after Science’s review of sensitivity analysis methods in 1989 (System analysis at mo...
We present two methods for the estimation of main effects in global sensitivity analysis. The method...
A new method for sensitivity analysis of model output is introduced. It is based on the Fourier Ampl...
Some recent articles, all in volume 102 of JGR, Atmosphere, use sensitivity analysis (SA) for mechan...
We present computational tools to analyse some key properties of DSGE models and address the followi...
Climate policy decisions rely heavily on the predictions of climate–economic models. These models ar...
Motivated by an application in the realm of climate change economics,we develop and prove the mathem...
Sensitivity analysis assesses the influence of input parameters on the conclusion of a model. Tradit...
AbstractThe majority of published sensitivity analyses (SAs) are either local or one factor-at-a-tim...
Abstract Sensitivity analysis is an essential paradigm in Earth and Environmental Systems modeling. ...