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A multiple linear regression (MLR) model was constructed as benchmark for the comparison of performances.
First, we apply a multiple linear regression (MLR) to identify the most representative rating (MRR).
In PCR a multiple linear regression is performed on principal components.
To predict the difficulty of PAC placement from the factors, a multiple linear regression was conducted.
A multiple linear regression (MLR) calibration equation was developed using a set of 41 calibration samples.
A multiple linear regression analysis is performed to benchmark the GP model with a classical technique.
To create a sensible comparison, a multiple linear regression (MLR) model was also developed.
Selected variables are used to build usability models based on a multiple linear regression technique.
As a comparison, a multiple linear regression (MLR) analysis was also examined using various statistical indices.
A multiple linear regression analysis showed that the E. coli concentrations along the river were positively correlated with phosphorus.
A multiple linear regression model using the variable CF-PDI as the criterion is shown in Table 3.
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