Robust Linear Model Objects
These are objects of class lmRob
which represent the robust fit of a linear regression model, as estimated by lmRob
function.
coefficients |
vector of coefficients for the robust regression. If |
T.coefficients |
the vector of coefficients for the initial estimate, if |
scale |
the scale estimate computed using the initial estimates. |
residuals |
the residual vector corresponding to the estimates returned in |
T.residuals |
the residual vector corresponding to the estimates returned in |
fitted.values |
the fitted values corresponding to the estimates returned in |
T.fitted.values |
the fitted values corresponding to the estimates returned in |
cov |
the estimated covariance matrix of the estimates in |
T.cov |
the estimated covariance matrix of the estimates in |
rank |
the rank of the design matrix |
iter.refinement |
the number of iterations required to refine the initial estimates. |
df.residuals |
the degrees of freedom in the residuals (the number of rows in |
est |
a character string that specifies the type of estimates returned. If |
control |
a list of control parameters, passed to the function |
genetic.control |
a list of control parameters, passed to the function |
dev |
the robust deviance if final MM-estimates are returned. |
T.dev |
the robust deviance corresponding to initial S-estimates if applies. |
r.squared |
the fraction of variation in |
T.r.squared |
the fraction of variation in |
M.weights |
the robust estimate weights corresponding to the final MM-estimates in |
T.M.weights |
the robust estimate weights corresponding to the initial S-estimates in |
iter.final.coef |
the number of iterations required to compute the final MM-estimates of the coefficients, if applies. |
call |
an image of the call that produced the object, but with the arguments all named and with the actual formula included as the |
assign |
the same as the |
contrasts |
the same as the |
terms |
the same as the |
This class of objects is returned from the lmRob
function.
The following components must be included in a legitimate "lmRob"
object:
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