delay_model: Fit a delayed Exponential or Weibull model to one or two given sample(s).

Description

Maximum product of spacings estimation is used by default to fit the parameters. Estimation via naive maximum likelihood (method = 'MLEn) is available, too, but MLEn yields biased estimates. MLEc is a corrected version of MLE due to Cheng.

Usage

delay_model(
  x = stop("Specify observations for at least one group x=!", call. = FALSE),
  y = NULL,
  distribution = c("exponential", "weibull"),
  twoPhase = FALSE,
  bind = NULL,
  ties = c("density", "equidist", "random", "error"),
  method = c("MPSE", "MLEn", "MLEw", "MLEc"),
  profiled = method == "MLEw",
  optim_args = NULL,
  verbose = 0
)

Value

incubate_fit the delay-model fit object. Or NULL if optimization failed (e.g. too few observations).

Arguments

x: numeric. observations of 1st group. Can also be a list of data from two groups.
y: numeric. observations from 2nd group
distribution: character. Which delayed distribution is assumed? Exponential or Weibull.
twoPhase: logical. Allow for two phases?
bind: character. parameter names that are bind together in 2-group situation.
ties: character. How to handle ties.
method: character. Which method to fit the model? 'MPSE' = maximum product of spacings estimation or 'MLEn' = naive maximum likelihood estimation or 'MLEw' = weighted MLE' or MLEc' = corrected MLE
profiled: logical. Profile out scale from log-likelihood if possible.
optim_args: list. optimization arguments to use. Use NULL to use the data-dependent default values.
verbose: integer. level of verboseness. Default 0 is quiet.

Details

Numerical optimization is done by stats::optim.