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--- sensitivity_analysis_toolbox_example_-_cow [2022/09/29 12:44]
mina old revision restored (2022/09/27 12:51)
+++ sensitivity_analysis_toolbox_example_-_cow [2023/03/06 13:37]
mina
@@ Line 58: / Line 58: @@
 **Selection of Sensitivity analysis method**
-|{{:sensitivityanalysismethod.png?400|}}|Go to **Method** tab to open the [[Sensitivity_analysis_method_view|Sensitivity analysis method view]]. Here, the [[Sensitivity_analysis_methods|Sensitivity analysis method]] and its settings is selected.\\ \\ //Select the method Probabilistic with the following settings:\\ \\ Base sample size: 1000\\ Sampling type: Latin Hypercube\\ Calculate second order indices: Unchecked\\ Seed: Auto\\ //|
+|{{:sensitivityanalysismethod.png?400|}}|Go to **Method** tab to open the [[Sensitivity_analysis_method_view|Sensitivity analysis method view]]. Here, the [[Sensitivity_analysis_in_Ecolego#Methods|sensitivity analysis method]] and its settings is selected.\\ \\ //Select the method Probabilistic with the following settings:\\ \\ Base sample size: 1000\\ Sampling type: Latin Hypercube\\ Calculate second order indices: Unchecked\\ Seed: Auto\\ //|
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@@ Line 104: / Line 104: @@
 //Now, select C<sub>beef</sub> and click [[Correlation_pie_chart|Correlation pie chart]]//\\
 \\
-A [[Correlation_pie_chart|Correlation pie chart]] is created and for C<sub>milk</sub> and displays the first order sensitivity index of all parameters on the selected output. The same can be done for C<sub>beef</sub>. Select the Transformation from the drop down list under the table and put it on Rank.\\
+A [[Correlation_pie_chart|Correlation pie chart]] is created and for C<sub>milk</sub> and displays the first order sensitivity index of all parameters on the selected output. The same can be done for C<sub>beef</sub>. Right click on the Chart and click on Edit. In the Data tab, select the Transformation and put it on Rank.\\
 \\
 As seen in the chart and table, C_beef is most sensitive to TF_beef and C_milk the most sensitive to F_milk (both having a first order index of approximately 0.80. F_air also contribute a first order index of approximately 0.10. All other numbers are zero or very close to zero. The coefficient of determination R2 is close to 1 (0.96) and is an indication that the output samples are nearly linear in terms of the inputs samples. This implies that there should not be any significant contribution of higher order sensitivity indices (measuring interacting parameters). This conclusion is also supported by the very small (2%) //unexplained// part of the pie chart (for a perfect linear relationship, all first order sensitivity indices should sum to 1 leaving zero unexplained part).\\

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