Robust Linear Model Objects

DESCRIPTION:

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

GENERATION:

This class of objects is returned from the lmRobMM 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 "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.

SEE ALSO:

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