Gamma distribution maximum likelihood estimation

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

mlnaka(x, na.rm = FALSE, rel.tol = .Machine$double.eps^0.25,
  iterlim = 100)

Arguments

x	a (non-empty) numeric vector of data values.
na.rm	logical. Should missing values be removed?
rel.tol	Relative accuracy requested.
iterlim	A positive integer specifying the maximum number of iterations to be performed before the program is terminated.

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.

Examples

mlgamma(precip)
#> Maximum likelihood estimates for the Gamma model 
#>  shape    rate  
#> 4.7171  0.1352