weighted_IQR

Weighted (normalized) interquartile range

Robust (outlier-resistant) estimators of finite population
characteristics like of means, totals, ratios, regression, etc. Available
methods are M- and GM-estimators of regression, weight reduction,
trimming, and winsorization. The package extends the 'survey'
<https://CRAN.R-project.org/package=survey> package.

Tobias Schoch

robsurvey

Robust Survey Statistics Estimation

Beat Hulliger

Martin Sterchi

R-core 

weighted_IQR function

<dl> <dt>x</dt>
<dd><code>[numeric vector]</code> data.</dd> <dt>w</dt>
<dd><code>[numeric vector]</code> weights (same length as <code>x</code>).</dd> <dt>na.rm</dt>
<dd><code>[logical]</code> indicating whether <code>NA</code> values
 should be removed before the computation proceeds
 (default: <code>FALSE</code>).</dd> <dt>constant</dt>
<dd><code>[double]</code> constant scaling factor to make the
 weighted IQR a consistent estimator of the scale
 (default: <code>0.7413</code>).</dd></dl>

Arguments

Weighted Interquartile Range (IQR) — weighted_IQR

<dl>

 <dt>x</dt>
<dd><code>[numeric vector]</code> data.</dd>

 <dt>w</dt>
<dd><code>[numeric vector]</code> weights (same length as <code>x</code>).</dd>

 <dt>na.rm</dt>
<dd><code>[logical]</code> indicating whether <code>NA</code> values
 should be removed before the computation proceeds
 (default: <code>FALSE</code>).</dd>

 <dt>constant</dt>
<dd><code>[double]</code> constant scaling factor to make the
 weighted IQR a consistent estimator of the scale
 (default: <code>0.7413</code>).</dd>

</dl>

weighted_IQR: Weighted Interquartile Range (IQR)

Description

Usage

Value

Arguments

Details

See Also

Examples