Differences

This shows you the differences between two versions of the page.

--- what_is_sensitivity_analysis [2022/09/14 14:15]
mina
+++ what_is_sensitivity_analysis [2023/03/02 11:16] (current)
boris
@@ Line 14: / Line 14: @@
 \\
 //Local and global sensitivity analysis//
-Sensitivity analysis aims at determining how sensitive the model output is to changes in model inputs. When input parameters are relatively certain, we can look at the partial derivative of the output function with respect to the input parameters. This sensitivity measure can easily be computed numerically by performing multiple simulations varying input-parameters around a nominal value. We will find out the local impact of the parameters on the model output and therefore techniques like these are called local sensitivity analysis. For environmental and health risk assessments, input parameters will often be uncertain and therefore local sensitivity analysis techniques will not be usable for a quantitative analysis. We want to find out which of the uncertain input parameters are more important in determining the uncertainty in the output of interest. To find this we need to consider global sensitivity analysis, which are usually implemented using Monte Carlo (MC) simulation and are, therefore, called sampling-based methods.\\
+ aims at determining how sensitive the model output is to changes in model inputs. When input parameters are relatively certain, we can look at the partial derivative of the output function with respect to the input parameters. This sensitivity measure can easily be computed numerically by performing multiple simulations varying input-parameters around a nominal value. We will find out the local impact of the parameters on the model output and therefore techniques like these are called local sensitivity analysis. For environmental and health risk assessments, input parameters will often be uncertain and therefore local sensitivity analysis techniques will not be usable for a quantitative analysis. We want to find out which of the uncertain input parameters are more important in determining the uncertainty in the output of interest. To find this we need to consider global sensitivity analysis, which are usually implemented using Monte Carlo (MC) simulation and are, therefore, called sampling-based methods.\\
 \\
@@ Line 22: / Line 22: @@
 Different sensitivity analysis techniques will do well on different types of model problems. At an initial phase, for models with a large amount of uncertain input parameters, a screening method could be used to qualitatively find out which the most important parameters are and which are not important. The screening method implemented in EIKOS is the Morris design //(Morris, 1991)//. A natural starting point in the analysis with sampling-based methods would be to examine scatter plots. With these, the modeller can graphically find out nonlinearities, nonmonotonicity and correlations between the inputoutput parameters.
-**See also**
-  * [[Sensitivity_analysis_toolbox_wiki|Sensitivity analysis toolbox wiki]]
-  * [[eikos_help.pdf|MATLAB Eikos help document]]
 //References//
@@ Line 33: / Line 29: @@
 Morris, 1991. Max D. Morris. Parameterial sampling plans for preliminary computational experiments. Technometrics, 33(2):161–174, May 1991.
+**See also**
+  * [[Sensitivity_analysis_toolbox_wiki|Sensitivity analysis toolbox Wiki]]

Ecolego Wiki

User Tools

Site Tools

Differences

Page Tools