Sentence examples for recalculated model from inspiring English sources

Multiway sensitivity analyses from both perspectives recalculated model results using upper and lower input ranges for each purpose and duration of travel (Tables 1– 3).

We then recalculated the model 5000 times for each of six scenarios for the effect of screening on breast cancer incidence used to construct the life tables.

In order to investigate the effect that the addition of MITF and c-FOS would have to the predictive power of GAM, we then recalculated our model including these two factors (see Supplementary Fig S4 and Supplementary Tables S8 and S9).

Does the model need to be adjusted, perhaps by changing the size of the model Sun (and if so, recalculate the model sizes and distances)?

To simulate a knockout, the expression level of the target gene was set to zero and expression values of objective genes were recalculated using models from Eq. 1.

22 This calculation involved replacing all fixed input parameters used in the model by appropriate probability distributions and repeatedly recalculating the model output with values sampled from the defined input distributions.

The quadratic model was then adjusted by backward elimination: taking out terms that had no significant contribution (P > 0.05) one by one and then recalculating the model with the remaining terms.

We used Monte Carlo simulation to estimate the uncertainty around the point estimate of incremental costs and effects of GRT versus expert opinion by sampling 5000 times from all input distributions and then recalculating the model using specialized software (TreeAge Pro 2005, TreeAge Software Inc., Williamstown, USA).

The starting point was a quadratic model which was then adjusted by backward elimination: taking out terms that had no significant contribution (P > 0.05) one by one, and then recalculating the model with the remaining terms.

This analysis involved recalculating the model after sampling independently each parameter from an underlying distribution that reflects the degree of uncertainty in the parameter estimate (web appendix, web fig 1).

Permutation tests randomly assign samples to classes and recalculate the model: the random reassignments of samples to classes are repeated for a large number of times in order to ascertain the likelihood of the actual results being obtained by chance.