Sentence examples for by using partial regression from inspiring English sources

We tested this by using partial regression to statistically remove the effect of water depth and longitude.

We used partial regression plots to graphically display the results of the multiple GLS analyses [ 74].

Aggarwal et al.[82] show that good, bad, ugly pairs can be predicted by using partial least square regression between image-based features (sharpness, hue, and intensity) and geometric attributes of a face (obtained using active appearance modeling).

Both the calibration and the validation values obtained by using partial least squares (PLS2) regression method, indicate a good-quality model performance (slope near 1, off set near 0 and large correlation between sensors and categorized variables).

Cellular condition could be assessed by the metabolite composition using principal component analysis (PCA), and the relationship between cell densities and the metabolite composition, reflecting transition from exponential to stationary phases, could be understood by using partial least squares (PLS) regression (Fig.  1e).

We analyzed the real-time quantitative PCR data by multivariate regression using partial least square regression (PLSR) [23] with time after feeding as the predictor variable and relative quantity of bacteria as the response variable.

Results were obtained by cross-validation using partial least squares regression; ASI: Australian Selection Index; PPT: protein percentage GEBV predictions for bulls born between 1998 and 2002 were calculated by combining the MBV predictions with the sire maternal-grandsire pathway predictions, which were calculated at the time of birth of the young bull calves (Table 6).

All spectra were treated by computational tools for multivariate analysis using partial least squares regression (PLS) on the software program Pirouette 3.11 (Infometrix, Inc .. Variable selections were performed by the QSAR modeling program.

The calibration models were constructed using Partial Least Square regression (PLS-1) and Multiple Linear Regression (MLR).

The relationships among pore characteristics and Dr were analyzed using partial least squares regression (PLSR).

The predictive potential of OES is evaluated using partial least square regression (PLSR) analysis.