r2() internally calls the appropriate function for the given model. In case of mixed models this will be r2_nakagawa(). r2_nakagawa() computes the marginal and conditional r-squared values, while icc() calculates an adjusted and conditional ICC, both based on the proposals from Nakagawa et ...
After fitting, R provides the r.squared value: summary = summary(m) # The R^2 value that lm provides r2 = summary$r.squared # 0.993019 How exactly is this value computed? I know that for linear models using ordinary (unweighted) least squares, this value is computed as R2=1−(y...
codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 #> #> Residual standard error: 2.057 on 498 degrees of freedom #> Multiple R-squared: 0.8553, Adjusted R-squared: 0.855 #> F-statistic: 2943 on 1 and 498 DF, p-value: < 2.2e-16 cor(dat$y,dat$...
mse1 sets the mean squared error to 1, forcing the variance–covariance matrix of the estimators to be (X X)−1 (see Methods and formulas below) and affecting calculated standard errors. Degrees of freedom for t statistics is calculated as n rather than n − k. coeflegend; see [R]...
The sharpness controls how much blur should bleed over edges. Y BlurNumPasses int Default is 44. On lowest quality level default is 22. Y BilateralSigmaSquared float Only affects downsampled SSAO. Higher values create a larger blur. Y BilateralSimilarityDistanceSigma float Onl...
[0.14, 1.00]### - One-sided CIs: upper bound fixed at [1.00].epsilon_squared(model)## # Effect Size for ANOVA### Parameter | ε² | 95% CI## ---## factor(gear) | 0.39 | [0.14, 1.00]### - One-sided CIs: upper bound fixed at [1.00]. And more… Effect Size Conversion...
mse1 sets the mean squared error to 1, forcing the variance–covariance matrix of the estimators to be (X X)−1 (see Methods and formulas below) and affecting calculated standard errors. Degrees of freedom for t statistics is calculated as n rather than n − k. coeflegend; see [R]...