Variable importance measured as the scaled mean decrease in accuracy of each variable in the Baseline and Extended model. A higher value confers a higher decrease in the accuracy of the model, should that variable be omitted.</p
<p>Measures of variable importance, population data included in the covariates.</p
<p><i>Importance</i>-variable importance calculated as one minus the correlation between the model o...
<p>Variable importance for the distributional and biological traits from the random forest analysis ...
<p>Variable importance ranked according to the mean decrease in accuracy using the RF OOB samples.</...
Variable importance values for prediction of outcome, using full parent data set (Higher value indic...
<p>Importance refers to Relative Importance: the proportion of explained variance attributable to ea...
<p>Variable importance for analysis 1 (including proportion of L2 speakers, circles) and analysis 2 ...
<p>Importance was calculated based on mean decrease in model accuracy (black bars) and mean decrease...
Overall variable importance for both under and over-predicted areas from the RF model.</p
Jackknife test showing the importance of each variable independently, when building the Maxent model...
<p><i>Footnote.</i> Numerical values represent % increase in mean squared error if variable is omitt...
Importance of variables as measured by partial Wald χ2 minus the predictor degrees of freedom in the...
<p>Selected model coefficients, confidence interval and relative importance of the variables used.</...
Variable importance plot showing the decrease in singular value inertia attributable to each predict...
<p>Higher values define more important variables. Values higher than 0.50 are in boldface.</p
<p>Measures of variable importance, population data included in the covariates.</p
<p><i>Importance</i>-variable importance calculated as one minus the correlation between the model o...
<p>Variable importance for the distributional and biological traits from the random forest analysis ...
<p>Variable importance ranked according to the mean decrease in accuracy using the RF OOB samples.</...
Variable importance values for prediction of outcome, using full parent data set (Higher value indic...
<p>Importance refers to Relative Importance: the proportion of explained variance attributable to ea...
<p>Variable importance for analysis 1 (including proportion of L2 speakers, circles) and analysis 2 ...
<p>Importance was calculated based on mean decrease in model accuracy (black bars) and mean decrease...
Overall variable importance for both under and over-predicted areas from the RF model.</p
Jackknife test showing the importance of each variable independently, when building the Maxent model...
<p><i>Footnote.</i> Numerical values represent % increase in mean squared error if variable is omitt...
Importance of variables as measured by partial Wald χ2 minus the predictor degrees of freedom in the...
<p>Selected model coefficients, confidence interval and relative importance of the variables used.</...
Variable importance plot showing the decrease in singular value inertia attributable to each predict...
<p>Higher values define more important variables. Values higher than 0.50 are in boldface.</p
<p>Measures of variable importance, population data included in the covariates.</p
<p><i>Importance</i>-variable importance calculated as one minus the correlation between the model o...
<p>Variable importance for the distributional and biological traits from the random forest analysis ...
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