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Under the assumption that the relationship between the target variable being downscaled and the available covariates can be nonlinear, dissever uses weighted generalised additive models (GAMs) to drive the empirical function.
aWith partial diagrams the association between the target variable and a specific predicting variable is investigated without including the effect of the other predicting variables on the target variable.
A model for the relationship between the target variable and one or more auxiliary variable(s) can adequately conform to the trend in Y. Auxiliary data are commonly available for all population elements.
All gave more efficient results than the use of simple random sampling as long as there was some positive level of correlation between the target variable of the inventory and the auxiliary variable being used; their efficiency increased progressively as the level of correlation increased.
R Statistics 2.14 (R Development Core Team, Vienna, Austria) was used to calculate the Pearson correlation between the target variable (NTD incidences) and the area proportion of each type of soils and lithodological classes across a series of buffer distances (from 20 m to 3 km).
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In the following the correlations between the target variables and the sintering parameters were discussed and summarised in a model.
The software applies the support vector machines (SVM) algorithm and provides a classification analysis by optimizing a hyperplane between the target variables.
For the analysis of evolutionary relationships between the target variables we used CAIC 2.6.9[ 35] (available at [ 36]).
The structural part, that is the part describing the relation between the target variables, did not significantly differ between individuals with managerial function and individuals without.
Using SPSS 21 [ 89] for descriptives and Mplus 7.11 [ 90] for Structural Equation Modeling (SEM), we examined the relationships between the target variables.
Machine learning methods were used to find possible explanations of associations between the target variables (personality traits) and biological indicators of occupational Hg exposure in combination with covariables on the subgroup level.
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