Sentence examples for small regression from inspiring English sources
Recent studies [8, 9] indicate that the interpretation of linear SVM models is possible for small regression data sets.
begin{aligned} varvec{beta } = (mathbf {X}^mathrm{{T}}mathbf {X})^{-1}mathbf {X}^mathrm{{T}}mathbf {y} end{aligned} (2)A large regression coefficient does not imply that the factor is significantly influencing the response and a small regression coefficient does not imply that the factor is not influencing the response.
Although small regression coefficients might be biologically relevant, this indicates that there are also many spurious results amongst the small regression weights.
We also found small regression coefficients in the Black-Caribbean children, although these were not significantly different from the Dutch.
The relatively small regression coefficients and effect sizes affect the evaluation of these interrelations and limit statistical power.
The study-specific interaction regression coefficients covered a wide range (i.e., we observed small regression coefficients and large within-study variances), suggesting that some random errors may have reduced study power.
As shown in Flynn et al. (2015) higher efficiency in the design can be associated with smaller regression coefficients, suggesting either weaker preferences or lower choice consistency [49].
Countries with the smallest regression coefficients for gender are Canada, Denmark and the United States (b = 0.79, 0.80 and 0.81, respectively), all corresponding to odds ratios of approximately 2.2.
SAR models were all statistically significant, at 99% confidence level, and showed greater explanatory powers and smaller regression coefficients, meaning that part of IMD was indeed explained by the spatial proximity of observations.
The introduction of S will assign smaller regression weights to the genes whose expression data exhibit large variance compared to the genes with small variance.
We assigned 1 point to the smallest regression coefficient and serving it as the least common denominator for assigning point values for the score items; then we rounded it up to the next integer as described by Le Gal and colleagues [25].
