Hi,

Not sure if this is a gretl issue or an econometric one actually.
I'm trying to come up with a script that replicates Stata's "rreg" command which is basically a robust estimation for outliers correction. It is based on an iterative WLS resulting in an optimal weight vector.

Now, for testing purposes, I'm running OLS and WLS models successively. I note that the WLS' "Statistics based on the original data" SSR and S.E of regression are slightly different from the respective OLS' output (in bold below). Should these parts of outputs be the same? 
If not, hhat is the difference coming from ?

Best,
Artur
 

? ols crime X
Model 1: OLS, using observations 1-50
Dependent variable: crime
...
Mean dependent var   566.6600   S.D. dependent var   295.8773
Sum squared resid     2442333   S.E. of regression   227.9573
...

? wls W crime X
Model 2: WLS, using observations 1-50
Dependent variable: crime
Variable used as weight: W
   ...
Statistics based on the weighted data:
Sum squared resid     1925024   S.E. of regression   202.3807
...
Statistics based on the original data:
Mean dependent var   566.6600   S.D. dependent var   295.8773
Sum squared resid     2469623   S.E. of regression   229.2273