The following components must be included in a legitimate
"lmRobMM"
object:
VALUE:
coefficients
vector of coefficients for the robust regression. If the bias is greater
than the expected bias (given the significance level,
level), then
coefficients
contains the initial S-estimates; otherwise it contains final
M-estimates.
T.coefficients
the coefficient not selected by the robust regression procedure. This is the
set of estimates, either the initial S-estimates, or the final M-estimates,
not returned in the vector
coefficients.
scale
the scale estimate computed using the initial S-estimates. For theoretical
reasons this is always preferred.
T.scale
the scale estimate computed using the final M-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.
M.weights
the robust estimate weights corresponding to the estimates returned in
coefficients
.
T.M.weights
the robust estimate weights 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.
dev
the deviance corresponding to the estimates in
coefficients.
T.dev
the deviance corresponding to the estimates in
T.coefficients.
r.squared
the fraction of variation in
y explained by the robust regression on
x
corresponding to the estimates in
coefficients.
T.r.squared
the fraction of variation in
y explained by the robust regression on
x
corresponding to the estimates in
T.coefficients.
mm.bias
a list describing the test of bias for final M-estimates, with the
following components:
stat, the t-statistic;
pchi, the probability that
a chi-squared random variable with degrees of freedom equal to
rank is
smaller than
stat;
qchi, the quantile of the chi-squared distribution
with degrees of freedom equal to
rank corresponding to the probability
input in the level (
level).
ls.bias
a list describing the test of bias for LS-estimates, with the following
components:
stat, the t-statistic;
pchi, the probability that a
chi-squared random variable with degrees of freedom equal to
rank is
smaller than
stat.
iter.refinement
the number of iterations required to refine the initial resampling
approximation of the S-estimates.
iter.final.coef
the number of iterations required to compute the M-estimates of the
coefficients from the initial S-estimates.
iter.final.scale
the number of iterations required to compute the final scale estimates given
the final coefficient estimates.
est
a character string that specifies the type of estimates returned. If
est="initial"
, the initial S-estimates are returned; if
est="final", the
final M-estimates are returned.
robust.control
a list of control parameters, passed to the function
lmRobMM as the
robust.control
argument that produced the
lmRobMM object.
genetic.control
a list of control parameters, passed to the function
lmRobMM as the
genetic.control
argument that produced the
lmRobMM object, if present.
df.residuals
the degrees of freedom in the residuals (the number of rows in
x minus
the rank of
x).
qr
the components of the QR-decomposition of the matrix
x, (only returned if
qr.out
is
TRUE).
rank
the rank of the design matrix
x.
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.