This class of objects is returned by the
survReg function
to represent a fitted parametric survival model.
Objects of this class have methods for the functions
print,
summary
,
predict, and
residuals.
COMPONENTS:
The following components must be included in a legitimate
survReg object.
ARGUMENTS:
coefficients
the coefficients of the
linear.predictors, which multiply the
columns of the model
matrix.
It does not include the estimate of error (sigma).
The names of the coefficients are the names of the
single-degree-of-freedom effects (the columns of the
model matrix).
If the model is over-determined there will
be missing values in the coefficients corresponding to non-estimable
coefficients.
icoef
coefficients of the baseline model, which will contain the intercept
and log(scale), or multiple scale factors for a stratified model.
var
the variance-covariance matrix for the parameters, including the log(scale)
parameter(s).
loglik
a vector of length 2, containing the log-likelihood for the baseline and
full models.
iter
the number of iterations required.
linear.predictors
the linear predictor for each subject.
df
the degrees of freedom for the final model. For a penalized model
this will be a vector with one element per term.
scale
the scale factor(s), with length equal to the number of strata.
idf
degrees of freedom for the initial model.
means
a vector of the column means of the coefficient matrix.
dist
the distribution used in the fit.
df.residual
the number of observations minus the sum of the degrees of freedom.
Needed by the
anova.survReg routine.
The object will also have the following components found in
other model results (some are optional):
linear predictors,
weights,
x,
y,
model,
call,
terms and
formula.
See
lm.object.