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
.
The following components must be included in a legitimate survreg
object.
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.
coefficients of the baseline model, which will contain the intercept and log(scale), or multiple scale factors for a stratified model.
the variance-covariance matrix for the parameters, including the log(scale) parameter(s).
a vector of length 2, containing the log-likelihood for the baseline and full models.
the number of iterations required
the linear predictor for each subject.
the degrees of freedom for the final model. For a penalized model this will be a vector with one element per term.
the scale factor(s), with length equal to the number of strata.
degrees of freedom for the initial model.
a vector of the column means of the coefficient matrix.
the distribution used in the fit.
included for a weighted fit.
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
.
survreg
, lm