Sentence examples for predictor models from inspiring English sources

We fitted multiple predictor models using automated model selection via information theoretic approaches and multi-model averaging using maximum likelihood.

Best predictor models are significantly improved when the influences of elevation, coastal effects and urban structure are added.

The data set of year 2002 was used to develop the ANFIS models as wave predictor models.

Actual weather and interruption data can be used to train the predictor models, and then theoretical weather data can be entered into the trained models.

These models are called Random Predictor Models (RPMs) because the predicted output corresponding to any given input is a random variable.

Because the correlation was strongest between MWD and each canopy structure variable (Fig. 4), we excluded AMI, CovP and MAP from subsequent multiple predictor models.

First, single-predictor models were calculated to assess the strength of each variable as a predictor of annual grass cover.

Cattle disturbance ranks are the third strongest predictor among the single-predictor models, behind latitude and elevation.

Latitude and elevation each account for about 5% of deviance when used in single-predictor models and are retained in the rich-predictor model.

To quantify whether predictors identified as important in above multiple-predictor models improved the conditional R2 of MWD based models (see Fig. 4 for details), we directly added MinT to the models predicting LAI and FCover from MWD and we added Ele_Min and Slope to the MWD based model predicting fAPAR.

For interpretation of specific environmental effects we focus on single-predictor environmental relationships as high collinearity of environmental variables (Table 1) hampers the interpretation of multi-predictor models.