Global sensitivity analysis for complex ecological models: a case study of riparian cottonwood population dynamics

2011 ◽  
Vol 21 (4) ◽  
pp. 1225-1240 ◽  
Author(s):  
Elizabeth B. Harper ◽  
John C. Stella ◽  
Alexander K. Fremier
Keyword(s):  
Sensitivity Analysis ◽  
Population Dynamics ◽  
Global Sensitivity Analysis ◽  
Ecological Models ◽  
Global Sensitivity

scholarly journals An efficient protocol for the global sensitivity analysis of stochastic ecological models

Ecosphere ◽  
2016 ◽  
Vol 7 (3) ◽  
Author(s):  
Thomas A. A. Prowse ◽  
Corey J. A. Bradshaw ◽  
Steven Delean ◽  
Phillip Cassey ◽  
Robert C. Lacy ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Ecological Models ◽  
Global Sensitivity

A Methodology for Global Sensitivity Analysis of Activated Sludge Models: Case Study with Activated Sludge Model No. 3 ( ASM 3)

2019 ◽  
Vol 91 (9) ◽  
pp. 865-876
Author(s):  
Dhan Lord B. Fortela ◽  
Kyle Farmer ◽  
Alex Zappi ◽  
Wayne W. Sharp ◽  
Emmanuel Revellame ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Activated Sludge ◽  
Global Sensitivity Analysis ◽  
Activated Sludge Model ◽  
Global Sensitivity ◽  
Activated Sludge Models

scholarly journals Variable Selection in Regression Models Using Global Sensitivity Analysis

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
William Becker ◽  
Paolo Paruolo ◽  
Andrea Saltelli
Keyword(s):  
Sensitivity Analysis ◽  
Variable Selection ◽  
Regression Models ◽  
Global Sensitivity Analysis ◽  
Physical Models ◽  
Model Fit ◽  
Global Sensitivity ◽  
Testing Sequence ◽  
Input Variables

Abstract Global sensitivity analysis is primarily used to investigate the effects of uncertainties in the input variables of physical models on the model output. This work investigates the use of global sensitivity analysis tools in the context of variable selection in regression models. Specifically, a global sensitivity measure is applied to a criterion of model fit, hence defining a ranking of regressors by importance; a testing sequence based on the ‘Pantula-principle’ is then applied to the corresponding nested submodels, obtaining a novel model-selection method. The approach is demonstrated on a growth regression case study, and on a number of simulation experiments, and it is found competitive with existing approaches to variable selection.

scholarly journals Global sensitivity analysis to optimize basin-scale conductive model calibration – A case study from the Upper Rhine Graben

Geothermics ◽  
2021 ◽  
Vol 95 ◽  
pp. 102143
Author(s):  
Denise Degen ◽  
Karen Veroy ◽  
Jessica Freymark ◽  
Magdalena Scheck-Wenderoth ◽  
Thomas Poulet ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Model Calibration ◽  
Global Sensitivity Analysis ◽  
Upper Rhine Graben ◽  
Global Sensitivity ◽  
Rhine Graben ◽  
Basin Scale ◽  
Upper Rhine
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