Sentence examples for relative prediction from inspiring English sources

Annual herbage dry matter intake per cow and hectare, both per year, were predicted with RMSPE, relative prediction error, and concordance correlation coefficient of 169 and 692 kg of dry matter, 3 and 4%, and 0.91 and 0.87, respectively.

Indeed, we observe that the relative prediction error (i.e., the difference between predicted and true locations normalized by the distance between the true ancestry locations, see the section Materials and Methods) decreases with the distance between ancestries in Europe.

Statistical measures of model performance and associated graphical analysis of the final specifications indicated that the models performed well in terms of accounting for a relatively large proportion of variation (61 88%), unbiasedness and predictive ability (e.g., temporal invariant patterns in absolute and relative prediction errors).

The predictive performance of the formula was evaluated by computing the mean relative prediction error (me%= N−1∑ j =1 N (pej) where N is the number of patients=15) as a measure of bias and the root mean squared relative prediction error (rmse%=[ N−1∑ j =1 N (pej)]1/2) as an assessment of precision.

The objective of this paper was to implement three different geostatistical approaches that predict missing values of MP within the Kenyan HMIS to examine their relative prediction accuracies.

This is confirmed by computation of the mean relative prediction accuracy (see Figure 2).

Relative predictions can be made with greater accuracy.

Relative predictions, representing the spatial variability in sediment exports, were correctly represented by the model.

The relative predictions of the present model and the rational correlations have been presented for the estimation of plume length for both the types of jet systems.

While this is a relatively simple method that does not include compounding influences such as variation among species and latitudes, it nonetheless provides similar estimates to studies using more complex methods (e.g. [13]), and forms a standard baseline for relative predictions of increasing CCS under different scenarios of future habitat recovery.

Just as for experimental models in biology, relative predictions by in silico models may be more useful than absolute predictions.