ME version of tram::Survreg
SurvregME(
formula,
data,
subset,
weights,
offset,
na.action = na.omit,
dist = c("weibull", "logistic", "gaussian", "exponential", "rayleigh", "loggaussian",
"lognormal", "loglogistic"),
scale = 0,
silent = TRUE,
nofit = FALSE,
optim_control = list(outer = list(), optim = list()),
...
)an object of class "formula": a symbolic description
of the model structure to be
fitted. The details of model specification are given under
tram and in the package vignette.
an optional data frame, list or environment (or object
coercible by as.data.frame to a data frame) containing the
variables in the model. If not found in data, the
variables are taken from environment(formula).
an optional vector specifying a subset of observations to be used in the fitting process.
an optional vector of weights to be used in the fitting
process. Should be NULL or a numeric vector. If present,
the weighted log-likelihood is maximised.
this can be used to specify an _a priori_ known component to
be included in the linear predictor during fitting. This
should be NULL or a numeric vector of length equal to the
number of cases.
a function which indicates what should happen when the data
contain NAs. The default is set by the na.action setting
of options, and is na.fail if that is unset.
character defining the conditional distribution of the (not necessarily positive) response, current choices include Weibull, logistic, normal, exponential, Rayleigh, log-normal (same as log-gaussian), or log-logistic.
a fixed value for the scale parameter(s).
Logical, if TRUE, prints all tracing information.
Logical, if TRUE, creates the model objects, but does not run the optimization.
List of optional arguments for the optimizer.
additional arguments to tram.
A SurvregME object.
Fixing the scale parameter is currently not available.