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.

- 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.

- weights
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`