Fits a rsm model without computing the model matrix of the
response vector.
rsm.surv(X, Y, offset, family, dispersion, score.dispersion, maxit, epsilon,
trace, …)the model matrix (design matrix).
the response vector.
optional offset added to the linear predictor.
a family.rsm object, i.e. a list of functions and
expressions characterizing the error distribution. Families
supported are extreme (Gumbel or extreme value),
logWeibull, logExponential, logRayleigh,
logistic and student (Student's t) with df
\(>\) 2.
if NULL, the MLE of the scale parameter is
returned, otherwise the scale parameter is fixed to the numerical
value passed through the argument.
must default to NULL.
maximum number of iterations.
convergence threshold.
if TRUE, iterations details are printed during execution.
not used, but do absorb any redundant argument.
an object, which is a subset of a rsm object.
The rsm.surv function is called internally by the
rsm routine to do the actual model fitting. Although
it is not intended to be used directly by the user, it may be useful
when the same data frame is used over and over again. It might save
computational time, since the model matrix is not created. No
formula needs to be specified as an argument. As no weights
argument is available, the response Y and the model matrix
X must already include the weights if weighting is desired.