fit_elife: Fit excess lifetime models by maximum likelihood

In longevity: Statistical Methods for the Analysis of Excess Lifetimes

Fit excess lifetime models by maximum likelihood

Description

This function is a wrapper around constrained optimization routines for different models with non-informative censoring and truncation patterns.

Usage

fit_elife(
  time,
  time2 = NULL,
  event = NULL,
  type = c("right", "left", "interval", "interval2"),
  ltrunc = NULL,
  rtrunc = NULL,
  thresh = 0,
  status = NULL,
  family = c("exp", "gp", "weibull", "gomp", "gompmake", "extgp", "gppiece",
    "extweibull", "perks", "perksmake", "beard", "beardmake"),
  weights = NULL,
  export = FALSE,
  start = NULL,
  restart = FALSE,
  arguments = NULL,
  ...
)

Arguments

time	excess time of the event of follow-up time, depending on the value of event
time2	ending excess time of the interval for interval censored data only.
event	status indicator, normally 0=alive, 1=dead. Other choices are TRUE/FALSE (TRUE for death). For interval censored data, the status indicator is 0=right censored, 1=event at time, 2=left censored, 3=interval censored. Although unusual, the event indicator can be omitted, in which case all subjects are assumed to have experienced an event.
type	character string specifying the type of censoring. Possible values are "right", "left", "interval", "interval2".
ltrunc	lower truncation limit, default to NULL
rtrunc	upper truncation limit, default to NULL
thresh	vector of thresholds
status	integer vector giving status of an observation. If NULL (default), this argument is computed internally based on type.
family	string; choice of parametric family
weights	weights for observations
export	logical; should data be included in the returned object to produce diagnostic plots? Default to FALSE.
start	vector of starting values for the optimization routine. If NULL, the algorithm attempts to find default values and returns a warning with false convergence diagnostic if it cannot.
restart	logical; should multiple starting values be attempted? Default to FALSE.
arguments	a named list specifying default arguments of the function that are common to all elife calls
...	additional parameters, currently ignored

Value

an object of class elife_par

Note

The extended generalized Pareto model is constrained to avoid regions where the likelihood is flat so \xi \in [-1, 10] in the optimization algorithm.

The standard errors are obtained via the observed information matrix, calculated using the hessian. In many instances, such as when the shape parameter is zero or negative, the hessian is singular and no estimates are returned.

Examples

data(ewsim, package = "longevity")
fit1 <- fit_elife(
   arguments = ewsim,
   export = TRUE,
   family = "exp")
fit2 <- fit_elife(
   arguments = ewsim,
   export = TRUE,
   family = "gp")
plot(fit1)
summary(fit1)
anova(fit2, fit1)

longevity documentation built on Nov. 12, 2023, 5:07 p.m.