Log-gamma distribution maximum likelihood estimation

The maximum likelihood estimate of shapelog and ratelog are calculated by calling mlgamma() on the transformed data.

Usage

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

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.

Examples

mllgamma(precip)
#> Maximum likelihood estimates for the Loggamma model 
#> shapelog   ratelog  
#>    35.90     10.43