Sentence examples for both models were considered from inspiring English sources

For the prediction of SPEI-1 (1-month), the errors associated with both models were considered relatively high.

In this study both models were considered to complement genealogical methods that fail to detect signs of a spatial expansion.

Scoring weights based on both models were considered and found to perform similarly, so a common set of scoring weights was used for the clinical items in both algorithms in order to ease comparison and application of the criteria.

To check this possibility for GMDH and ANN models, the effect of various parameters on response of both models was considered.

Both models are considered to be valid and able to predict the SADT of organic peroxides through rigorous model validations.

Both models are considered to be suitable for studies of this type.

Both models are considered nonparametric and depend strongly on the statistical approach that optimizes the extrapolation of the training data when the sensitivity of image data layers to biomass is low.

We tested the dominance deviation for all the SNPs and we found that only one of the SNPs showed significant deviation from additivity, thus making the use of the assumption-free model unnecessary, although, as a general rule, we suggest that both models are considered initially.

Both the models were considered for a fixed-effects analysis (as per the previous identifiability analysis reported by Evans et al).

Variables that showed significant associations from both forward and backward models were considered independent risk factors.

In single SNP analyses, homozygosity for the more frequent allele among controls was defined as the reference group and both additive and dominant models were considered.