Uses Newton-Raphson to estimate the parameters of the Gamma distribution.

## Arguments

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

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

- ...
`rel.tol`

is the relative accuracy requested, defaults to`.Machine$double.eps^0.25`

.`iterlim`

is a positive integer specifying the maximum number of iterations to be performed before the program is terminated (defaults to`100`

).

## Value

`mlgamma`

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`

## Details

For the density function of the Gamma distribution see GammaDist.

## References

Choi, S. C, and R. Wette. "Maximum likelihood estimation of the parameters of the gamma distribution and their bias." Technometrics 11.4 (1969): 683-690.

Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 17. Wiley, New York.

## See also

GammaDist for the Gamma density.