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.