When running a linear regression using sparklyr, such as:
cached_cars %>% ml_linear_regression(mpg ~ .) %>% summary()
The results do not include standard errors
Deviance Residuals: Min 1Q Median 3Q Max -3.47339 -1.37936 -0.06554 1.05105 4.39057 Coefficients: (Intercept) cyl_cyl_8.0 cyl_cyl_4.0 disp hp drat 16.15953652 3.29774653 1.66030673 0.01391241 -0.04612835 0.02635025 wt qsec vs am gear carb -3.80624757 0.64695710 1.74738689 2.61726546 0.76402917 0.50935118 R-Squared: 0.8816 Root Mean Squared Error: 2.041
- Is there a way to display standard errors when running this regression?
- Is there a way to cluster standard errors in sparklyr?
- I have also been trying to run a linear model with multiple group fixed effects in sparklyr. In base R, I have done so with felm. Does anyone have experience doing this in sparklyr?
Solutions using SparkR are also highly appreciated.