help mregress 


mregress -- Huber regression M-estimator


mregress depvar [indepvars] [if] [in] [, options]

options Description ------------------------------------------------------------------------- Model noconstant suppress constant term tune(#) use # as Huber M-tuning constant; default is tune(7)

Reporting level(#) set confidence level; default is level(95)


mregress performs a Huber M-estimator of regression of depvar on indepvars. The command is a slight modification of rreg where only Huber's iterations are considered

Also see [R] regress for standard regression with robust variance estimates and [R] qreg for quantile (including median or least-absolute-residual) regression.


+-------+ ----+ Model +------------------------------------------------------------

tune(#) is the Huber tuning constant. Lower tuning constants downweight outliers rapidly but may lead to unstable estimates (less than 6 is not recommended). Higher tuning constants produce milder downweighting. See [R] rreg for further details.

+-----------+ ----+ Reporting +--------------------------------------------------------

level(#); see [R] estimation options.


Setup . sysuse auto . generate weightd = weight*(foreign==0) . generate weightf = weight*(foreign==1)

Robust regression . mregress mpg weightd weightf foreign

Saved results

mmregress saves the following in e():

Scalars e(N) number of observations e(mss) model sum of squares e(df_m) model degrees of freedom e(rss) residual sum of squares e(df_r) residual degrees of freedom e(r2) R-squared e(r2_a) adjusted R-squared e(F) F statistic e(rmse) root mean squared error

Macros e(cmd) rreg e(cmdline) command as typed e(depvar) name of dependent variable e(title) title in estimation output e(model) ols e(properties) b V e(predict) program used to implement predict

Matrices e(b) coefficient vector e(V) variance-covariance matrix of the estimators

Functions e(sample) marks estimation sample

Also see

Online: [R] qreg, [R] regress; [R] rreg, mmregress, sregress, msregress, mcd