Sentence examples for more predictors in from inspiring English sources

Similarly, the performance of the current model may be improved if we consider more predictors in the model although this will also increase the complexity of the model.

In some cases, having two or more predictors in the same subset led to the occurrence of cells with very low frequencies of observations.

Nevertheless, a study with a larger sample size will enable the simultaneous evaluation of more predictors in the future and may help confirm our findings.

When SF models were based on high stringency of marker selection (P = 1e-04), aggregating of the appropriately thinned maps (2 ∼5 cM inter-marker distances) seemed to slightly improve model fit by incorporating more predictors in the ensemble.

However, this may be attributable in part to differences in population characteristics and intervention methods, and thus a larger sample size is required when detecting more predictors in the future.

In statistics, multicollinearity is a situation in which two or more predictor variables in a multiple regression model are highly correlated, meaning that one can be linearly predicted from the others with a non-trivial degree of accuracy.3Both the Variance Inflation Factor (VIF) method and Correlation Coefficient Table are commonly used for the test, as well in this paper.

For ULM the numbers of predictors with a λ within a defined bin are shown in Tables 3 and 4. A higher marker density results in more predictors that are less smoothed, i.e. showing a λ closer to one.

Hence, some replicates might show several big QTL resulting in more predictors with a large λ whereas other replicates might show only small or medium sized QTL and the number of predictors with a λ close to one is small in these replicates as well.

We found that traffic indicators not reliant on ADT estimates (i.e. roadway lengths) provided more stable predictors in the residential settings in our study.

In these conditions, meteorologic parameters in stage 1 have less predicting power in the non-AOD model than in the AOD model, and land use variables are more effective predictors in stage 2 of the non-AOD model.

Multigenic markers consist of several differentially expressed genes which also form a connected region in protein protein interaction (PPI) networks and proved to be more stable predictors in cross-platform evaluation schemes.