mlgumbel: Gumbel distribution maximum likelihood estimation

In univariateML: Maximum Likelihood Estimation for Univariate Densities

Description

Uses Newton-Raphson to estimate the parameters of the Gumbel distribution.

Usage

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

Arguments

x	a (non-empty) numeric vector of data values.
na.rm	logical. Should missing values be removed?
...	sigma0 is an optional starting value defaulting to 1. rel.tol is the relative accuracy requested, defaults to .Machine$double.eps^0.25. iterlim is a positive integer specifying the maximum number of iterations to be performed before the program is terminated (defaults to 100).

Details

For the density function of the Gumbel distribution see Gumbel.

Value

mlgumbel returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for mu and s 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

shape and sigma.

References

Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 2, Chapter 22. Wiley, New York.

See Also

Gumbel for the Gumbel density.

Examples

mlgumbel(precip)

Example output

Maximum likelihood estimates for the Gumbel model 
   mu  sigma  
27.89  13.76  

univariateML documentation built on Jan. 25, 2022, 5:09 p.m.