| mlpareto {univariateML} | R Documentation |
Pareto distribution maximum likelihood estimation
Description
The maximum likelihood estimate of b is the minimum of x and the
maximum likelihood estimate of a is
1/(mean(log(x)) - log(b)).
Usage
mlpareto(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 Pareto distribution see Pareto.
Value
mlpareto returns an object of class univariateML.
This is a named numeric vector with maximum likelihood estimates for
a and b 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 20. Wiley, New York.
See Also
Pareto for the Pareto density.
Examples
mlpareto(precip)