Learn R Programming

univariateML (version 1.1.1)

mlinvgamma: Inverse Gamma distribution maximum likelihood estimation

Description

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

Usage

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

Value

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

Arguments

x

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

na.rm

logical. Should missing values be removed?

...

passed to mlgamma.

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

Run this code
mlinvgamma(precip)

Run the code above in your browser using DataLab