mlweibull: Weibull distribution maximum likelihood estimation

In univariateML: Maximum Likelihood Estimation for Univariate Densities

Description

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

Usage

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

Arguments

x	a (non-empty) numeric vector of data values.
na.rm	logical. Should missing values be removed?
...	shape0 is an optional starting value for the shape parameter. 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 Weibull distribution see Weibull.

Value

mlweibull returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for shape and scale 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

References

Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 21. Wiley, New York.

See Also

Weibull for the Weibull density.

Examples

BIC(mlweibull(precip))

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