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sensitivity_analysis [2024/03/27 11:12]
dmytroh 		sensitivity_analysis [2024/03/27 11:16]
dmytroh
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 ====== Sensitivity analysis ====== ====== Sensitivity analysis ======
  
-[[http://en.wikipedia.org/wiki/Sensitivity_analysis|Sensitivity analysis]] can be performed on probalistic simulation outputs (see [[Probabilistic_simulation|probabilistic_simulation]]). After a probabilistic Monte Carlo simulation, sensitivity indices can be calculated between simulation inputs (parameters) and simulation outputs (blocks).+[[http://en.wikipedia.org/wiki/Sensitivity_analysis|Sensitivity analysis]] can be performed on probalistic simulation outputs (see [[Probabilistic_simulation|probabilistic simulation]]). After a probabilistic Monte Carlo simulation, sensitivity indices can be calculated between simulation inputs (parameters) and simulation outputs (blocks).
  
 ===== Performing a sensitivity analysis ===== ===== Performing a sensitivity analysis =====
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 |Note|The [[Sensitivity_analysis_toolbox|sensitivity analysis toolbox]] offers many sensitivity analysis methods and several additional [[Chart|charts]].| |Note|The [[Sensitivity_analysis_toolbox|sensitivity analysis toolbox]] offers many sensitivity analysis methods and several additional [[Chart|charts]].|
  
-  - Run a probabilistic simulation as explained in [[Probabilistic_simulation|probabilistic_simulation]].+  - Run a probabilistic simulation as explained in [[Probabilistic_simulation|probabilistic simulation]].
   - Create [[Tornado_chart|tornado charts]] or [[Correlation_table|correlation tables]] to graphically display sensitivity indices. Seven different types of sensitivity indices are available in Ecolego.   - Create [[Tornado_chart|tornado charts]] or [[Correlation_table|correlation tables]] to graphically display sensitivity indices. Seven different types of sensitivity indices are available in Ecolego.
  
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 |Partial Rank Correlation Coefficient ([[PRCC|PRCC]])                |Computes the ranked correlation coefficient taking into account the rest of the varying parameters. Interesting when model is linearly or monotonically depending on parameters.| |Partial Rank Correlation Coefficient ([[PRCC|PRCC]])                |Computes the ranked correlation coefficient taking into account the rest of the varying parameters. Interesting when model is linearly or monotonically depending on parameters.|
 |EASI first order correlation coefficient ([[EASI|EASI]])            |Quantifies the first order effects, if model is additive this will take into account the full variance.                                                                         | |EASI first order correlation coefficient ([[EASI|EASI]])            |Quantifies the first order effects, if model is additive this will take into account the full variance.                                                                         |
-|XEASI Higher Order Sensitivity Indices([[XEASI|XEASI]])            |  |+|XEASI Higher Order Sensitivity Indices([[XEASI|XEASI]])            |XEASI indices can assist in model calibration and validation processes by revealing which parameters have the most substantial impact on model predictions.  
 +|
 ===== See also ===== ===== See also =====
  
sensitivity_analysis.txt · Last modified: 2024/03/27 11:16 by dmytroh

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