Sentence examples for model selection were from inspiring English sources

To avoid this bias, we devised a procedure by which the influential variables included in model selection were selected by their ability to explain variation within the data of interest (e.g. carbon storage).

Then statistics and model selection were performed.

The effects of DCE-MRI scan duration and protocol design (continuous vs integrated scanning) on the estimated pharmacokinetic (PK) parameters and on model selection, were studied using both simulated and patient data.

Statistical support for the parameter values and model selection were estimated through BayesFactors [54], calculated using the Tracer software [61] based on the harmonic mean of the likelihoods, calculated by the BayesTraits program.

Data partitioning and model selection were the same as for the MrBayes analyses described above.

"-" under model selection indicates that AIC and hLRT model selection were not applicable for the partition.

Backward model selection was performed to select risk factors for the final model.

The model selection is automated using Autometrics.

Our model selection was based on average loss.

On the second stage, acoustic model selection is performed.

The proposed model selection criterion is applied to arboreal marsupials data and model selection is carried out.