Sentence examples for linear regression resulted from inspiring English sources

Modelling of [Hb] using multivariate linear regression resulted in a best-fit model that explained 37.2% of the variability in [Hb] (Table 6).

Of note, estimating the samples growth rates directly from the gene expression data by using multiple linear regression, resulted in inferior performance (Supplementary file 1J), testifying to the added value of personalized GSMMs.

Regarding tuber yield and SCB, linear regression resulted in the repeated selection of significantly associated marker fragments from the L-galactono-1,4-lactone dehydrogenase and hydroxycinnamoyl CoA quinate transferase genes, respectively.

The regularised logistic regression resulted in REGS classifiers utilising 73 genes for C and 32 for O and regularised linear regression resulted in REGS predictors utilising 27 genes for C and 21 for O.

The linear regression resulted in values of R = 0.67 and 0.30 for the modeled dioxin I-TEQs in the urban and rural areas, respectively, and the corresponding values for sumPCBs of R = 0.60 and 0.11.

Predicting log10(θ r + 1) with linear regression resulted in negative θ r values; therefore we also tested the prediction performance while forcing θr to be equal to 0 in the case of negative values, and as another option used θ r predicted from MSs and RTs.

We suggest swapping the RSSI and the log(distance) axes and redoing the linear regression, resulting in the standard error on the logarithm of the distance.

This is thus a linear regression resulting in an over-determined system if the number of local grid points are sufficiently large.

Although in bivariate linear regression results the negative coefficients of depression, anxiety and PTSD symptoms were similar, multivariate linear regression showed that the coefficient for depression symptoms was greater than for the others.

This association is consistent with the multiple linear regression results for continuous term birth weight, in which mean birth weights were 5 24 g greater in the higher IDW well count exposure tertiles than the referent group.

The Au, SO and SO concentrations (in ng g 1), respectively, were computed by using the y = kx + d relationships of the linear regressions resulting from the external calibrations.