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

Usage

mlinvgamma(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

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

Details

For the density function of the inverse 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

See also

InvGamma for the Inverse Gamma density.

Examples

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