Sentence examples for R-squared are from inspiring English sources

In Fig. 8, the values of adjusted R-squared are shown for different amplitudes and frequencies when the constant is 0.0203.

However, values of pseudo R-squared are based on likelihood statistics from a model containing the independent variables versus a model containing a constant term only, rather than a comparison of fitted to observed values as obtained from linear regression models (31).

The proposed model provides the best correlation between process parameters and response (TWR) as the values of R-Squared and Adjusted R-Squared are 99.15% and 98.48% respectively.

As shown in Fig. 3, the three housing price linkage indices of beta, correlation, and R-squared are positively relevant to cultural similarity.

The outcomes indicate that the model is valid as the value of R-Squared and adjusted R-Squared are 98.77% and 98.58% respectively with no significant lack of fit.

All models are significant with Prob > F is less than 0.05, and the difference between predicted R-squared and adjustable R-squared is less than 0.2.

According to the results, the R-squared and adjusted R-squared were 0.982 and 0.964, respectively, implying that the model was statistically suitable.

R-squared and adjusted R-squared were calculated with the linear regression tool using ferritin, TML or BB as predictors and free carnitine or total carnitine as responses.

The Pred R-Squared and Adj R-Squared were 0.8002 and 0.9722, respectively; the Pred R-Squared was found to be in a reasonable agreement with the Adj R-Squared.

R-squared increased with more complex models, such as the age drift model's R-squared was increased over 50% compared to the age model.

The adjusted R-squared was between 50 and 75% in all the models, with the highest R-squared in models of all-cause morbidity.