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The maximum likelihood estimate of shape and rate are calculated by calling mlweibull on the transformed data.

Usage

mlinvweibull(x, na.rm = FALSE, ...)

Arguments

x

a (non-empty) numeric vector of data values.

na.rm

logical. Should missing values be removed?

...

passed to mlweibull.

Value

mlinvweibull returns an object of classunivariateML. 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

Details

For the density function of the log normal distribution see InverseWeibull.

References

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.

See also

InverseWeibull for the Inverse Weibull density.

Examples

mlinvweibull(precip)
#> Maximum likelihood estimates for the InverseWeibull model 
#>   shape     rate  
#> 1.55463  0.04282