Sentence examples for mean model error from inspiring English sources

MLR analyses revealed differential forcing on pCO2 across seascapes and hierarchical levels and a 33% reduction in mean model error with increased partitioning (from 18.5 μatm to 12.0 μatm pCO2).

Model accuracy becomes high as the mean model error decreases.

The mean model error becomes very low at a β factor of 1.

At a factor value of 4, the mean model error does not decrease monotonically with respect to the number of incorporated enzymes and the mean model error becomes larger than any other value of β.

In a factor range from 0.5 to 2, the mean model error decreases as the number of incorporated enzymes increases.

The allowable ranges of the model error were broad, but the mean model error for all the enzyme combinations decreased as the number of integrated enzymes increased.

The regression model proposed herein and the attendant statistics of the model error (mean, coefficient of variation and type of distribution) can be easily used in a reliability analysis procedure to assess safety levels implicit in different design procedures.

The main effects models have similar mean absolute errors, though it is slightly lower for the mean model.

Table 7 Nowcasting performance   Base model Google model Mean absolute error 29.559 15.059 Root mean squared error 41.564 34.59 Mean absolute percentage error 7.728 7.125 The Google model leads to lower errors than the base model, as evaluated by three different error metrics.

Using the variances of the estimated population means, and the correlation between auxiliary variables and the variable of interest, a design consistent regression estimator that has minimum model mean squared error under a working model is derived.

To determine the predictive precision of the models, we computed model mean square error (MSE) and mean absolute error (MAE).