Robust Linear Model Objects

DESCRIPTION:

These are objects of class lmRob which represent the robust fit of a linear regression model, as estimated by lmRob() function.

GENERATION:

This class of objects is returned from the lmRob function.

METHODS:

add1 , anova, coefficients, deviance, drop1, fitted.values, formula , labels, plot, print, residuals, summary, update.

STRUCTURE:

The following components must be included in a legitimate "lmRob" object:

VALUE:

coefficients
vector of coefficients for the robust regression. If est="final", these are final estimates; if est="initial", these are initial estimates.
T.coefficients
the vector of coefficients for the initial estimate, if est="final".
scale
the scale estimate computed using the initial estimates.
residuals
the residual vector corresponding to the estimates returned in coefficients .
T.residuals
the residual vector corresponding to the estimates returned in T.coefficients .
fitted.values
the fitted values corresponding to the estimates returned in coefficients.
T.fitted.values
the fitted values corresponding to the estimates returned in T.coefficients.
cov
the estimated covariance matrix of the estimates in coefficients.
T.cov
the estimated covariance matrix of the estimates in T.coefficients.
rank
the rank of the design matrix x.
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 x minus the rank of x).
est
a character string that specifies the type of estimates returned. If est="initial" , the initial estimates are returned; if est="final", the final estimates are returned.
robust.control
a list of control parameters, passed to the function lmRob as the robust.control argument that produced the lmRob object.
genetic.control
a list of control parameters, passed to the function lmRob as the genetic.control argument that produced the lmRob object, if present.
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 y explained by the robust regression on x corresponding to the final MM-estimates in coefficients, if applies.
T.r.squared
the fraction of variation in y explained by the robust regression on x corresponding to the initial S-estimates in T.coefficients, if applies.
M.weights
the robust estimate weights corresponding to the final MM-estimates in coefficients , if applies.
T.M.weights
the robust estimate weights corresponding to the initial S-estimates in T.coefficients , if applies.
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 formula argument.
assign
the same as the assign component of an "lm" object.
contrasts
the same as the contrasts component of an "lm" object.
terms
the same as the terms component of an "lm" object.

SEE ALSO:

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