Object Reference : Object View and Procedure Reference : Equation
  
 
robustls
Equation Methods
Estimates an equation using robust least squares.
You may perform three different types of robust estimation: M-estimation, S-estimation and MM-estimation.
Syntax:
eq_name.robustls(options) y x1 [x2 x3…]
Enter the robustls keyword, followed by the dependent variable and a list of the regressors.
Options
 
method=arg (default=“m”)
Robust estimation method: “m” (M-estimation), “s” (S-estimation) or “mm” (MM-estimation).
cov=arg (default=“type1”)
Covariance method type: “type1”, “type2”, or “type3”.
tuning=number
Specify a value for the tuning parameter. If a value is not specified, EViews will use the default tuning parameter for the type of estimation and weighting function (if applicable).
c=s
Convergence criterion. The criterion will be set to the nearest value between 1e-24 and 0.2.
coef=arg
Specify the name of the coefficient vector (if specified by list); the default behavior is to use the “C” coefficient vector.
m=integer
Maximum number the number of iterations.
prompt
Force the dialog to appear from within a program.
p
Print results.
M-estimation Options
 
fn=arg (default=“bisquare”)
Weighting function used during M-estimation: “andrews” (Andrews), “bisquare” (Bisquare), “cauchy” (Cauchy), “fair”, “huber”, “huberbi” (Huber-bisquare), “logistic” (Logistic), “median”, “tal” (Talworth), “Welsch” (Welsch).
scale=arg (default=“madzero”)
Scaling method used for calculating the scalar parameter during M estimation: “madzero” (median absolute deviation, zero centered), “madmed” (median absolute deviation, median centered), "huber" (Huber scaling).
hmat
Use the hat-matrix to down-weight observations with high leverage.
S and MM estimation options
 
compare = integer (default=4)
Number of comparison sets.
refine = integer (default= 2)
Number of refinements.
trials = integer (default=200)
Number of trials.
subsmpl=integer
Specifies the size of the subsamples. Note, the default is number of coefficients in the regression.
seed=number
Specifies the random number generator seed
rng=arg
Specifies the type of random number generator. The key can be; improved Knuth generator (“kn”), improved Mersenne Twister (“mt”), Knuth’s (1997) lagged Fibonacci generator used in EViews 4 (“kn4”) L’Ecuyer’s (1999) combined multiple, recursive generator (“le”), Matsumoto and Nishimura’s (1998) Mersenne Twister used in EViews 4 (“mt4”).
MM estimation options
 
mtuning=arg
M-estimator tuning parameter.
Note the S-estimator tuning parameter is set with the “tuning=” option outlined above.
hmat
Use the hat-matrix to down-weight observations with high leverage during m-estimation.
Examples
The following examples use the “Rousseeuw and Leroy.wf1” file located in the EViews application data directory.
equation eq1.robustls salinity c lagsal trend discharge
This line estimates a simple M-type robust estimation, with SALINITY as the dependent variable, and a constant, LAGSAL, TREND and DISCHARGE as independent variables.
The line:
equation eq2.robustls(method=mm, tuning=2.937, mtuning=3.44, cov=type2) salinity c lagsal trend discharge
estimates the same model, but using MM-estimation, with an S tuning constant of 2.937, an M tuning constant of 3.44, and using Huber Type II standard errors.
Cross-references
See “Robust Least Squares” for discussion.