mlweibull

For the density function of the Weibull distribution see
<a href="/link/Weibull?package=univariateML&version=1.5.0" data-mini-rdoc="univariateML::Weibull">Weibull</a>.

User-friendly maximum likelihood estimation (Fisher (1921)
<doi:10.1098/rsta.1922.0009>) of univariate densities.

Jonas Moss

univariateML

Maximum Likelihood Estimation for Univariate Densities

Thomas Nagler

Chitu Okoli

mlweibull function

<dl><dt>x</dt>
<dd>a (non-empty) numeric vector of data values.</dd>
<dt>na.rm</dt>
<dd>logical. Should missing values be removed?</dd>
<dt>...</dt>
<dd><code>shape0</code> is an optional starting value for the <code>shape</code> parameter.
<code>reltol</code> is the relative accuracy requested, defaults
to <code>.Machine$double.eps^0.25</code>. <code>iterlim</code> is a positive integer
specifying the maximum number of iterations to be performed before the
program is terminated (defaults to <code>100</code>).</dd></dl>

Arguments

For the density function of the Weibull distribution see
<a href='https://rdrr.io/r/stats/Weibull.html'>Weibull</a>.

Weibull distribution maximum likelihood estimation — mlweibull

<dl>

<dt>x</dt>
<dd>a (non-empty) numeric vector of data values.</dd>


<dt>na.rm</dt>
<dd>logical. Should missing values be removed?</dd>


<dt>...</dt>
<dd><code>shape0</code> is an optional starting value for the <code>shape</code> parameter.
<code>reltol</code> is the relative accuracy requested, defaults
to <code>.Machine$double.eps^0.25</code>. <code>iterlim</code> is a positive integer
specifying the maximum number of iterations to be performed before the
program is terminated (defaults to <code>100</code>).</dd>

</dl>

mlweibull: Weibull distribution maximum likelihood estimation

Description

Usage

Value

Arguments

Details

References

See Also

Examples