Sensitivity analysis shows the model is sensitive to 2 model parameters both of which are concerned with the historic (pre-systematic) period of the time series.
One-way sensitivity analysis showed the model is sensitive to lurasidone and generic risperidone hospitalization rates.
Sensitivity analysis demonstrates that the model is sensitive to changes of three lumped parameters: K1+ (total affinity of stationary solid phase to contaminants), K2+ (total affinity of DOM to contaminants), and K3+ (total affinity of bacteria to contaminants).
The sensitivity analysis shows that the model is sensitive to parameter changes.
Indeed, the sensitivity analyses show that the model is sensitive to assumptions about coverage of services and level of reimbursement, and the gap between provider costs and reimbursement would increase significantly under differing assumptions.
As depicted in Figure 1, sensitivity analysis on demand of customers shows that the proposed model is sensitive to demand of customers.
The sensitivity analysis provided in the previous section showed that the developed model is sensitive to changes in the important reservoir parameters affecting oil production.
In addition, the one-way sensitivity analyses for the discount rate and effectiveness reveal that the model is sensitive to changes of the programme effectiveness, even though most parameters were distributed probabilistically.
Therefore, this model is sensitive to noise in the input speech.
On the contrary, the width of our proposed model is sensitive to squared coefficient of variation.
Results suggest the model is sensitive to the key hydrological parameter soil hydraulic conductivity.
