mts_plot

<code>mts_plot</code> constructs a plot of a MTS. Each univariate series comprising
the MTS object is displayed in a different colour.

An implementation of several machine learning algorithms for
multivariate time series. The package includes functions allowing the
execution of clustering, classification or outlier detection methods,
among others. It also incorporates a collection of multivariate time
series datasets which can be used to analyse the performance of new
proposed algorithms. Some of these datasets are stored in GitHub data
packages 'ueadata1' to 'ueadata8'. To access these data packages, run
'install.packages(c('ueadata1', 'ueadata2', 'ueadata3', 'ueadata4', 'ueadata5', 'ueadata6', 'ueadata7', 'ueadata8'), repos='<https://anloor7.github.io/drat/>')'.
The installation takes a couple of minutes but we strongly encourage the
users to do it if they want to have available all datasets of mlmts.
Practitioners from a broad variety of fields could
benefit from the general framework provided by 'mlmts'.

Angel Lopez-Oriona

mlmts

Machine Learning Algorithms for Multivariate Time Series

Jose A. Vilar

mts_plot function

<dl><dt>series</dt>
<dd>A MTS (numerical matrix).</dd>
<dt>title</dt>
<dd>Title for the plot (string). Default corresponds to no title.</dd></dl>

Arguments

Ángel López-Oriona, José A. Vilar

Author

Constructs a plot of a MTS — mts_plot

<dl>

<dt>series</dt>
<dd>A MTS (numerical matrix).</dd>


<dt>title</dt>
<dd>Title for the plot (string). Default corresponds to no title.</dd>

</dl>

mts_plot: Constructs a plot of a MTS

Description

Usage

Value

Arguments

Author

Details

Examples