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GQSAR models were derived using multiple linear regressions analysis.
Multiple linear regressions were applied to develop the models.
These retention times were modelled by stepwise multiple linear regressions.
The model was successfully fitted by multiple linear regressions.
This study was performed using multiple linear regressions (MLRs) and an artificial neural network (ANN).
The most relevant of these descriptors were grouped and multiple linear regressions have been carried out.
Differences between heuweltjie zones were assessed with ANOVAs and multiple linear regressions.
The collected data has been analyzed with simple and multiple linear regressions and structural equation model.
These metrics were used as explanatory variables in multiple linear regressions to explain aesthetic judgments.
These response variables were fitted to predictive models applying multiple linear regressions.
The parameters of the models were estimated by multiple linear regressions.
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