Description Usage Arguments Details Value Author(s) References See Also Examples
Robust estimation for Seemingly Unrelated Regression Models in presence of cellwise and casewise outliers performed using a threestage procedure. In the first step estimation of the coefficients in each singleequation model is obtained using a Robust Regression procedure, robust estimation of the residual covariance is obtained by a TwoStep Generalized Sestimator, a weighted least square is performed on the whole system to get final estimates of the regression coefficients.
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formula 
a list of objects of class 
data 
a list of objects of class 
control 
list of control parameters. The default is constructed
by the function 
... 
arguments passed to the function

x 
an object of class 
digits 
number of digits to print. 
The estimation of systems of equations with unequal numbers of observations is not implemented.
surerob
returns a list of the class surerob
and
contains all results that belong to the whole system.
This list contains one special object: "eq". It is a list and contains
one object for each estimated equation. These objects are of the class
lmrob
and contain the results that belong only to the
regarding equation.
The objects of the class surerob
have the following components:
eq 
a list that contains the results that belong to the individual equations. 
call 
the matched call. 
method 
estimation method. 
rank 
total number of linear independent coefficients. 
coefficients 
vector of all estimated coefficients. 
fitted.values 
matrix of fitted values. 
residuals 
matrix of residuals 
imp.residuals 
imputed residuals from 
residCovEst 
residual covariance matrix used for estimation. 
residCov 
estimated residual covariance matrix. 
rweights 
matrix of robust weights. 
TSGS 
object from function 
control 
list of control parameters used for the estimation. 
df.residual 
degrees of freedom of the whole system. 
y 
response observations used in the second step. 
x 
design matrix used in the second step. 
Claudio Agostinelli and Giovanni Saraceno
Giovanni Saraceno, Fatemah Alqallaf and Claudio Agostinelli (2021?) A Robust Seemingly Unrelated Regressions For RowWise And CellWise Contamination, submitted
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