winsorize

Winsorizing a vector means that a predefined quantum of the smallest
and/or the largest values are replaced by less extreme values.
Thereby the substitute values are the most extreme retained values.

Auxiliary package for better/faster analytics, visualization, data mining, and machine
learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling,
Marketing Mix Modeling (Robyn), Exploratory, API, and Scrapper, it helps the analyst or
data scientist to get quick and robust results, without the need of repetitive coding or
advanced R programming skills.

Bernardo Lares

lares

Analytics & Machine Learning Sidekick

winsorize function

<dl><dt>x</dt>
<dd>Numeric vector. Distribution to be winsorized.</dd>
<dt>thresh</dt>
<dd>Numeric vector. Lower and upper quantiles thresholds.
Set values within [0,1].</dd>
<dt>na.rm</dt>
<dd>Boolean. Should <code>NA</code> be omitted to calculate the quantiles?
Note that <code>NA</code> in <code>x</code> are preserved and left unchanged anyway.</dd></dl>

Arguments

Outliers: Winsorize — winsorize

<dl>

<dt>x</dt>
<dd>Numeric vector. Distribution to be winsorized.</dd>


<dt>thresh</dt>
<dd>Numeric vector. Lower and upper quantiles thresholds.
Set values within [0,1].</dd>


<dt>na.rm</dt>
<dd>Boolean. Should <code>NA</code> be omitted to calculate the quantiles?
Note that <code>NA</code> in <code>x</code> are preserved and left unchanged anyway.</dd>

</dl>

winsorize: Outliers: Winsorize

Description

Usage

Value

Arguments

See Also