| mlinvgauss {univariateML} | R Documentation |
Inverse Gaussian (Wald) maximum likelihood estimation
Description
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. |
Details
For the density function of the Inverse Gamma distribution see InverseGaussian.
Value
mlinvgauss returns an object of class
univariateML. 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 |
References
Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 15. Wiley, New York.
See Also
InverseGaussian for the Inverse Gaussian density.
Examples
mlinvgauss(precip)