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

## 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`

).

## 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`

## Details

For the density function of the Weibull distribution see Weibull.

## 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))
#> [1] 573.3096
```