| survreg.object(survival4) | R Documentation |
This class of objects is returned by the `survreg' function to represent a fitted parametric survival model. Class `survreg' inherits from class `glm', since it is fit by iterative reweighted least squares; the object returned has all the components of a weighted least squares object.
Objects of this class have methods for the functions `print', `summary', `predict', and 'residuals'.
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 inestimable
coefficients.
|
parms |
the parameters of the model that are not coefficients of the X matrix.
The first of these will always be log(sigma).
|
fixed |
a vector of the same length as parms, where 1 indicates a parameter that
was fixed at its starting value and was not part of the iteration.
|
deviance |
minus twice the difference between the maximized log-likelihood under the fitted model and a saturated model. Similar to the residual sum of squares. |
loglik |
the log-likelihood for the final model. |
null.deviance |
the deviance corresponding to the model with only an itercept term, and
with parms fixed at their final values.
|
dresiduals |
the deviance residuals. |
var |
the final variance matrix, including both coefficients and free parameters. |
family |
a 2 element character vector giving the name of the family and
the link; mainly for printing purposes.
The object will also have the components of an |
The following components must be included in a legitimate survreg object.
The residuals, fitted values, coefficients and effects should be extracted
by the generic functions of the same name, rather than
by the "$" operator.
survreg, glm.object, lm.object.