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Except for the prediction of topsoil clay content, in all cases regression kriging model "C" performed best.
In most of the considered cases, regression trees and ensemble methods were able to provide very accurate predictions.
In four of six cases, regression trees identified a few days each year that accounted for a large percentage of the total annual movement, and thus offered a practical means to determine when road-closure events designed to minimize road mortality of pond-breeding amphibians during migratory events would be most effectively employed.
In both cases, regression coefficients quantify potential effects on the specific parameter (mean or quantile) of the outcome distribution on a population level.
In all cases, regression slopes were very close to unity and intercepts were practically zero, attesting to the high accuracy of quantification.
In all cases, regression of posterior disease was documented by RetCam fundus photographs.
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In all cases, regressions obtained by using unit branch lengths achieved the best fit.
In this case, regression coefficients do not reach significance levels but the signs of the coefficients of all variables indicate a negative impact of consolidation on job finding rates, irrespective how consolidation is measured.
In this case, regression models are useful to predict RF-EMF exposure for different population strata.
In comparison with worst-case regression, it reduces the estimation variability and is able to produce reasonable estimation results even when regression on incomplete datasets is inapplicable.
Network inference methods can be split into five categories based on the underlying model in each case: regression, mutual information, correlation, Boolean regulatory networks, and other techniques [ 152].
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