Inverse Gamma distribution maximum likelihood estimation

Transforms the data and uses Newton-Raphson to estimate the parameters of the Gamma distribution.

mlinvgamma(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

A named numeric vector with maximum likelihood estimates for alpha and beta.

Details

For the density function of the Gamma distribution see InvGamma.

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. Witkovsky, V. (2001). "Computing the Distribution of a Linear Combination of Inverted Gamma Variables". Kybernetika. 37 (1): 79–90

Examples

mlinvgamma(precip)
#> Maximum likelihood estimates for the InvGamma model 
#>  alpha    beta  
#>  3.074  80.971