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

mlweibull(x, na.rm = FALSE, shape0 = 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? |

shape0 | 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. |

`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`

For the density function of the Weibull distribution see Weibull.

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

Weibull for the Weibull density.

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