detect_outliers

This function detects outliers/anomalies in the data. If the
<code>replace_outlier</code> argument is set to <code>TRUE</code>, then the outliers are removed
and imputed using the provided imputation methods.

A reliable and efficient tool for cleaning univariate time
series data. It implements reliable and efficient procedures for
automating the process of cleaning univariate time series data.
The package provides integration with already developed and deployed
tools for missing value imputation and outlier detection. It also
provides a way of visualizing large time-series data in different
resolutions.

Mayur Shende

cleanTS

Testbench for Univariate Time Series Cleaning

Neeraj Bokde

Andrés E. Feijóo-Lorenzo

detect_outliers function

<dl><dt>dt</dt>
<dd>A data.table.</dd>
<dt>replace_outlier</dt>
<dd>Boolean, defaults to <code>TRUE</code>. Specify if the outliers
are to be removed and imputed.</dd>
<dt>imp_methods</dt>
<dd>The imputation methods to be used.</dd></dl>

Arguments

Find outliers in the data — detect_outliers

<dl>

<dt>dt</dt>
<dd>A data.table.</dd>


<dt>replace_outlier</dt>
<dd>Boolean, defaults to <code>TRUE</code>. Specify if the outliers
are to be removed and imputed.</dd>


<dt>imp_methods</dt>
<dd>The imputation methods to be used.</dd>

</dl>

detect_outliers: Find outliers in the data

Description

Usage

Value

Arguments