I have the following linear model:
To address the residuals heteroscedasticity I have tried to apply a log transformation on the dependent variable as $\log(Y + 1)$ but I still see the same fan out effect on the residuals. The DV values are relatively small so the +1 constant addition before taking the log is probably not appropriate in this case.
> summary(Y) Min. :-0.0005647 1st Qu.: 0.0001066 Median : 0.0003060 Mean : 0.0004617 3rd Qu.: 0.0006333 Max. : 0.0105730 NA's :30.0000000
How can I transform the variables to improve the prediction error and variance, particularly for the far right fitted values?