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:
modelThe name of the model.
densityThe density associated with the estimates.
logLikThe loglikelihood at the maximum.
supportThe support of the density.
nThe number of observations.
callThe 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.