The maximum likelihood estimate of `shapelog`

and `ratelog`

are calculated
by calling `mlgamma()`

on the transformed data.

## Arguments

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

- na.rm
logical. Should missing values be removed?

- ...
passed to

`mlgamma`

.

## Value

`mllgamma`

returns an object of class`univariateML`

.
This is a named numeric vector with maximum likelihood estimates for
`shapelog`

and `ratelog`

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 Loggamma.

## References

Hogg, R. V. and Klugman, S. A. (1984), Loss Distributions, 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

Loggamma for the log normal density.