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* _______________________________________________ Gretl-users mailing list -- gretl-users(a)gretlml.univpm.it To unsubscribe send an email to gretl-users-leave(a)gretlml.univpm.it Website: https://gretlml.univpm.it/postorius/lists/gretl-users.gretlml.univpm.it/

Am 21.12.2020 um 13:17 schrieb Artur Bala: Well, it should be the different estimators, no?