MachineShop (version 2.2.0)

SurvRegModel: Parametric Survival Model

Description

Fits the accelerated failure time family of parametric survival models.

Usage

SurvRegModel(
  dist = c("weibull", "exponential", "gaussian", "logistic", "lognormal",
    "logloglogistic"),
  scale = NULL,
  parms = NULL,
  ...
)
SurvRegStepAICModel(
  dist = c("weibull", "exponential", "gaussian", "logistic", "lognormal",
    "logloglogistic"),
  scale = NULL,
  parms = NULL,
  ...,
  direction = c("both", "backward", "forward"),
  scope = NULL,
  k = 2,
  trace = FALSE,
  steps = 1000
)

Arguments

dist

assumed distribution for y variable.

scale

optional fixed value for the scale.

parms

list of fixed parameters.

...

arguments passed to survreg.control.

direction

mode of stepwise search, can be one of "both" (default), "backward", or "forward".

scope

defines the range of models examined in the stepwise search. This should be a list containing components upper and lower, both formulae.

k

multiple of the number of degrees of freedom used for the penalty. Only k = 2 gives the genuine AIC; k = .(log(nobs)) is sometimes referred to as BIC or SBC.

trace

if positive, information is printed during the running of stepAIC. Larger values may give more information on the fitting process.

steps

maximum number of steps to be considered.

Value

MLModel class object.

Details

Response Types:

Surv

Default values for the NULL arguments and further model details can be found in the source link below.

See Also

psm, survreg, survreg.control, stepAIC, fit, resample

stepAIC, fit, resample

Examples

# NOT RUN {
library(survival)

fit(Surv(time, status) ~ ., data = veteran, model = SurvRegModel)

# }