help mregress 
-------------------------------------------------------------------------------

Title

    mregress --   Huber regression M-estimator


Syntax

        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)


Description

    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.


Options

        +-------+
    ----+ 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.



Examples

    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