mlinvgauss

a (non-empty) numeric vector of data values.

logical. Should missing values be removed?

na.rm

The maximum likelihood estimate of <code>mean</code> is the empirical mean and the
maximum likelihood estimate of <code>1/shape</code> is the difference between
the mean of reciprocals and the reciprocal of the mean.

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

mlinvgauss 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>currently affects nothing.</dd></dl>

Arguments

Inverse Gaussian (Wald) maximum likelihood estimation — mlinvgauss

<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>currently affects nothing.</dd>

</dl>

mlinvgauss: Inverse Gaussian (Wald) maximum likelihood estimation

Description

Usage

Value

Arguments

Details

References

See Also

Examples