The maximum likelihood estimate of shape
and rate
are calculated
by calling mlweibull
on the transformed data.
mlinvweibull(x, na.rm = FALSE, ...)
mlinvweibull
returns an object of class
univariateML
. This is a named numeric vector with maximum likelihood
estimates for shape
and rate
and the following attributes:
model
The name of the model.
density
The density associated with the estimates.
logLik
The loglikelihood at the maximum.
support
The support of the density.
n
The number of observations.
call
The call as captured my match.call
a (non-empty) numeric vector of data values.
logical. Should missing values be removed?
passed to mlweibull
.
For the density function of the log normal distribution see InverseWeibull.
Kleiber, C. and Kotz, S. (2003), Statistical Size Distributions in Economics and Actuarial Sciences, Wiley.
Klugman, S. A., Panjer, H. H. and Willmot, G. E. (2012), Loss Models, From Data to Decisions, Fourth Edition, Wiley.
Dutang, C., Goulet, V., & Pigeon, M. (2008). actuar: An R package for actuarial science. Journal of Statistical Software, 25(7), 1-37.
InverseWeibull for the Inverse Weibull density.