For this sensitivity ratio, the difference in in vivo clearance predictions was divided by the percentage difference in the system-specific parameter.
The individual deviations from the prediction were divided by the standard error of the prediction, which is 1·30 cm in SGA children, 2 resulting in the studentized residuals.
In short, prediction is divided into smaller haplotype blocks that do not contain any switch errors, and QAN50 is N50 of divided inferred haplotypes with some adjustments.
Train and prediction are divided in two complex steps: (i) choosing a classifier, in which a model must be selected, trained, and tested, and (ii) parameter tuning, involving algorithms and techniques in order to fit the classifier parameters and obtain better results.
This resulted in 14,072 gene predictions that were divided by the 39 Mbp estimated genome size, which gave a gene density of approximately 2.77 ± 0.37 Kbp/gene or 0.36 ± 0.05 gene/Kbp for the genome of M. perniciosa.
Pocket prediction results were divided into different categories for quality assessment: Correct predictions were termed "TOP1-hits" whereas "TOP3-hits" are predictions where the respective ligand is found within the three largest predicted pockets.
When the prediction intervals were divided into quartiles according to the number of cases in the last observed period, the coverage level was inversely proportional to the frequency (84%, 52 %, 46 and 26%and26%
For the generation of prediction models, samples were divided into two groups as "training set" and "validation set" in such as way that each group had a similar composition of follow-up times since the first diagnosis.
All the predictions made by the model were divided by 1.27, which is the average of the ratios of model prediction to test result.
To investigate the difference in CVD risk prediction over fasting time, patients were divided into two groups, according to their postprandial time.
