delay_model {incubate} | R Documentation |
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
)
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 |
verbose |
integer. level of verboseness. Default 0 is quiet. |
Details
Numerical optimization is done by stats::optim
.
Value
incubate_fit
the delay-model fit object. Or NULL
if optimization failed (e.g. too few observations).