weighted_mean

Returns the weighted mean of a numeric vector.
In contrast to <code><a href="/link/stats%3A%3Aweighted.mean()?package=MetricsWeighted&version=1.0.4" data-mini-rdoc="MetricsWeighted::stats::weighted.mean()">stats::weighted.mean()</a></code>, <code>w</code> does not need to be specified.

Provides weighted versions of several metrics and performance
measures used in machine learning, including average unit deviances of
the Bernoulli, Tweedie, Poisson, and Gamma distributions, see
Jorgensen B. (1997, ISBN: 978-0412997112).  The package also contains
a weighted version of generalized R-squared, see e.g. Cohen, J. et al.
(2002, ISBN: 978-0805822236).  Furthermore, 'dplyr' chains are
supported.

Michael Mayer

MetricsWeighted

Weighted Metrics and Performance Measures for Machine Learning

Christian Lorentzen

weighted_mean function

<dl><dt>x</dt>
<dd>Numeric vector.</dd>
<dt>w</dt>
<dd>Optional vector of non-negative case weights.</dd>
<dt>...</dt>
<dd>Further arguments passed to <code><a href="/link/mean()?package=MetricsWeighted&version=1.0.4" data-mini-rdoc="MetricsWeighted::mean()">mean()</a></code> or <code><a href="/link/stats%3A%3Aweighted.mean()?package=MetricsWeighted&version=1.0.4" data-mini-rdoc="MetricsWeighted::stats::weighted.mean()">stats::weighted.mean()</a></code>.</dd></dl>

Arguments

Returns the weighted mean of a numeric vector.
In contrast to <code><a href='https://rdrr.io/r/stats/weighted.mean.html'>stats::weighted.mean()</a></code>, <code>w</code> does not need to be specified.

Weighted Mean — weighted_mean

<dl>

<dt>x</dt>
<dd>Numeric vector.</dd>


<dt>w</dt>
<dd>Optional vector of non-negative case weights.</dd>


<dt>...</dt>
<dd>Further arguments passed to <code><a href='https://rdrr.io/r/base/mean.html'>mean()</a></code> or <code><a href='https://rdrr.io/r/stats/weighted.mean.html'>stats::weighted.mean()</a></code>.</dd>

</dl>

weighted_mean: Weighted Mean

Description

Usage

Value

Arguments

See Also

Examples