univariateML (version 1.5.0)

mlburr: Burr distribution maximum likelihood estimation

Description

The maximum likelihood estimator fails to exist when the data contains no values strictly smaller than 1. Then the likelihood converges to the likelihood of the Pareto distribution in this case.

Usage

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

Value

mlburr returns an object of class

univariateML. This is a named numeric vector with maximum likelihood estimates for shape1 and shape2 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

Arguments

x

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

na.rm

logical. Should missing values be removed?

...

currently affects nothing.

Details

This function estimates the only the shape parameters of the Burr distribution. The shape is set to 1.

For the density function of the Burr distribution see Burr.

References

Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 20. Wiley, New York.

See Also

Burr for the Burr density.

Examples

mlburr(abalone$length)