The maximum likelihood estimate of mean is the empirical mean and the maximum likelihood estimate of 1/shape is the difference between the mean of reciprocals and the reciprocal of the mean.

## Usage

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

## Arguments

x

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

na.rm

logical. Should missing values be removed?

...

currently affects nothing.

## Value

mlinvgauss returns an object of classunivariateML. This is a named numeric vector with maximum likelihood estimates for mean and shape 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 Inverse Gamma distribution see InverseGaussian.

## References

Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 15. Wiley, New York.

mlinvgauss(precip)