Uses Newton-Raphson to estimate the parameters of the Gumbel distribution.
mlgumbel(x, na.rm = FALSE, sigma0 = 1, rel.tol = .Machine$double.eps^0.25, iterlim = 100)
x | a (non-empty) numeric vector of data values. |
---|---|
na.rm | logical. Should missing values be removed? |
sigma0 | An optional starting value for the |
rel.tol | Relative accuracy requested. |
iterlim | A positive integer specifying the maximum number of iterations to be performed before the program is terminated. |
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
For the density function of the Gumbel distribution see Gumbel.
Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 2, Chapter 22. Wiley, New York.
Gumbel for the Gumbel density.
mlgumbel(precip)#> Maximum likelihood estimates for the Gumbel model #> mu sigma #> 27.89 13.76