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sensitivity_analysis_toolbox_example_-_cow [2022/09/29 12:43] mina |
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A [[Correlation_table|Correlation table]] is created for the selected outputs, displaying the sensitivity indices calculated by the probabilistic method. Select the Transformation from the drop down list under the table and put it on Rank.\\ | A [[Correlation_table|Correlation table]] is created for the selected outputs, displaying the sensitivity indices calculated by the probabilistic method. Select the Transformation from the drop down list under the table and put it on Rank.\\ | ||
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- | //Now, select C< | + | //Now, select C< |
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- | A [[Correlation_pie_chart|Correlation pie chart]] is created and for C< | + | A [[Correlation_pie_chart|Correlation pie chart]] is created and for C< |
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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%) // | 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%) // |