Sentence examples for deviations in the model from inspiring English sources

Furthermore, Meeker [18] proposed several compromise plans, and the criterion that evaluates the ALT plan robustness to deviations in the model parameters and product life distribution.

Through computer experiment, over a wide range of values of γ0,e, γ1,e, and σe, and considering the deviations in the model parameters and life distribution, Meeker studied the actual efficiency of statistically optimal plans and compromise plans.

In general, model predictions were in good agreement with the experiments however some deviations in the model prediction were noted at the transition stage specifically for the water-glycerol system which was attributed to the liquid phase diffusional resistance not accounted in the present modelling framework.

The standard deviations in the models were found to be higher for small stores (22 to 24%) compared to larger stores (15%).

Although the six validated hydrological models had similar historical model performance (Nash Sutcliffe model efficiency coefficient (NSE) from 0.64 to 0.70), impact response surfaces derived using a scenario neutral approach demonstrated significant deviations in the models' responses to changes in future annual precipitation and temperature.

To solve these problems, Nelson [14, 15, 16, 17] suggested the use of a "compromise plan" with three or four stress levels, to enable the middle stress level to test the stress-life relationship, prevent test failures, and improve the plan robustness to the deviations in the statistical model and model parameters.

Thus, the absolute deviation in the model prediction from the perceived score is as less as 0.21 (i.e., 4.35 4.14).

The combined FFD and DS method successfully computed the propagation of the mean and standard deviation in the model, compared to the MC method.

This certainly introduces deviation in the model, but as we will discuss later, the experimental results can fit theoretical prediction well, suggesting that this simplicity is acceptable.

Cohen's d was calculated as the difference between predicted means from the final mixed-effects model for a given pair of groups divided by the estimated within-group error standard deviation in the model.

In general, the measured distances tended to display higher deviations in the smallest model as compared to B50 and B100.