Sentence examples for many candidate variables from inspiring English sources

Using Lasso penalized regression (to interpret key predictors from many candidate variables) and 10-fold cross-validation modelling (to indicate reproducibility and uncertainty), within different socio-geographic settings, our results show surrogate measures of landscape biodiversity correlate with respiratory health, and rank amongst known predictors.

As there were many candidate variables, the optimal approach we used was a stepwise multiple linear regression approach, progressively excluding variables, variables which explained minimal variance.

However, it was the first such study and included a careful analysis of many candidate variables including age, body mass index, varicose veins, use of hormone replacement therapy, family history of cardiovascular disease, oral contraceptive use, smoking status, educational attainment, reproductive history, and laboratory measurements, but no acute events such as surgery or immobilisation.

Existing datasets may also contain many more candidate variables than are really required to develop a good model, which can lead to multiple testing problems and a temptation to 'dredge' the data [ 6].

After performing sensitivity analysis of many candidate experiments, a latent variable model (PCA) is made from the resulting sensitivity matrix and the score matrix is used as a candidate set prior to experiment selection.

A number of the candidate variables, including many of the history and co-morbidity variables, were found to be insignificant, and we created a summary variable described above which included many of the highly significant variables from the index hospital admission (details available from authors).

Because of the large number of candidate variables (p = 22), many of which are correlated, and relatively small sample size (n = 10), the "elastic-net" method was used to identify important predictor variables.

They measured several clinical variables, collected fasting serum, and measured many candidate biomarkers from multiple diabetes-associated pathways.

We were somewhat surprised that none of the medication variables were included in the final model, despite looking at many candidate predictors.

Many factors both statistically and physically can affect the selection such as correlation between candidate variables and local hydrogeology conditions being overwhelmed by larger scale trends.

When the number of the experimental variables is large, the first and most critical step is to identify the (few) active factors among those (many) candidate factors.