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Among the output variables the number of vaccinations shows the widest variability.
The parameter sensitivity reflects the output variables' level of sensitivity to the parameter variation.
Based on the input variables, we can get the nodes' priority as the output variables.
Therefore the cumulant method can be adopted to obtain the numerical characteristics of the output variables.
In these statements, the output variables alone follow the template form write.
The convergence of the output variables is proved with Lyapunov theory for dynamic operating conditions.
Accordingly, the objective reduces to the unbiased estimation of the output variables.
This study focuses on the more realistic case, where only the output variables are measured.
It will show how much the output variables can vary when the input variables are changing.
Sensitivity analysis studies how the output variables are affected by input variables of a statistical model.
The output variables considered using the iterative process are the bulk, shear modulus and the thermal conductivity.
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