pyFTS/docs/html/pyFTS.benchmarks.html
2018-08-30 16:50:36 -03:00

1744 lines
120 KiB
HTML
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

<!doctype html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<title>pyFTS.benchmarks package &#8212; pyFTS 1.2.3 documentation</title>
<link rel="stylesheet" href="_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="_static/pygments.css" type="text/css" />
<script type="text/javascript" src="_static/documentation_options.js"></script>
<script type="text/javascript" src="_static/jquery.js"></script>
<script type="text/javascript" src="_static/underscore.js"></script>
<script type="text/javascript" src="_static/doctools.js"></script>
<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
<script type="text/javascript" src="_static/bizstyle.js"></script>
<link rel="index" title="Index" href="genindex.html" />
<link rel="search" title="Search" href="search.html" />
<link rel="next" title="pyFTS.common package" href="pyFTS.common.html" />
<link rel="prev" title="pyFTS package" href="pyFTS.html" />
<meta name="viewport" content="width=device-width,initial-scale=1.0">
<!--[if lt IE 9]>
<script type="text/javascript" src="_static/css3-mediaqueries.js"></script>
<![endif]-->
</head><body>
<div class="related" role="navigation" aria-label="related navigation">
<h3>Navigation</h3>
<ul>
<li class="right" style="margin-right: 10px">
<a href="genindex.html" title="General Index"
accesskey="I">index</a></li>
<li class="right" >
<a href="py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="right" >
<a href="pyFTS.common.html" title="pyFTS.common package"
accesskey="N">next</a> |</li>
<li class="right" >
<a href="pyFTS.html" title="pyFTS package"
accesskey="P">previous</a> |</li>
<li class="nav-item nav-item-0"><a href="index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="modules.html" >pyFTS</a> &#187;</li>
<li class="nav-item nav-item-2"><a href="pyFTS.html" accesskey="U">pyFTS package</a> &#187;</li>
</ul>
</div>
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
<div class="sphinxsidebarwrapper">
<p class="logo"><a href="index.html">
<img class="logo" src="_static/logo_heading2.png" alt="Logo"/>
</a></p>
<h3><a href="index.html">Table Of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">pyFTS.benchmarks package</a><ul>
<li><a class="reference internal" href="#module-pyFTS.benchmarks">Module contents</a></li>
<li><a class="reference internal" href="#submodules">Submodules</a></li>
<li><a class="reference internal" href="#module-pyFTS.benchmarks.benchmarks">pyFTS.benchmarks.benchmarks module</a></li>
<li><a class="reference internal" href="#module-pyFTS.benchmarks.Measures">pyFTS.benchmarks.Measures module</a></li>
<li><a class="reference internal" href="#module-pyFTS.benchmarks.ResidualAnalysis">pyFTS.benchmarks.ResidualAnalysis module</a></li>
<li><a class="reference internal" href="#module-pyFTS.benchmarks.Util">pyFTS.benchmarks.Util module</a></li>
<li><a class="reference internal" href="#module-pyFTS.benchmarks.arima">pyFTS.benchmarks.arima module</a></li>
<li><a class="reference internal" href="#module-pyFTS.benchmarks.knn">pyFTS.benchmarks.knn module</a></li>
<li><a class="reference internal" href="#module-pyFTS.benchmarks.naive">pyFTS.benchmarks.naive module</a></li>
<li><a class="reference internal" href="#module-pyFTS.benchmarks.quantreg">pyFTS.benchmarks.quantreg module</a></li>
</ul>
</li>
</ul>
<h4>Previous topic</h4>
<p class="topless"><a href="pyFTS.html"
title="previous chapter">pyFTS package</a></p>
<h4>Next topic</h4>
<p class="topless"><a href="pyFTS.common.html"
title="next chapter">pyFTS.common package</a></p>
<div role="note" aria-label="source link">
<h3>This Page</h3>
<ul class="this-page-menu">
<li><a href="_sources/pyFTS.benchmarks.rst.txt"
rel="nofollow">Show Source</a></li>
</ul>
</div>
<div id="searchbox" style="display: none" role="search">
<h3>Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="search.html" method="get">
<input type="text" name="q" />
<input type="submit" value="Go" />
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
</div>
</div>
<script type="text/javascript">$('#searchbox').show(0);</script>
</div>
</div>
<div class="document">
<div class="documentwrapper">
<div class="bodywrapper">
<div class="body" role="main">
<div class="section" id="pyfts-benchmarks-package">
<h1>pyFTS.benchmarks package<a class="headerlink" href="#pyfts-benchmarks-package" title="Permalink to this headline"></a></h1>
<div class="section" id="module-pyFTS.benchmarks">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.benchmarks" title="Permalink to this headline"></a></h2>
<p>pyFTS module for benchmarking the FTS models</p>
</div>
<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</div>
<div class="section" id="module-pyFTS.benchmarks.benchmarks">
<span id="pyfts-benchmarks-benchmarks-module"></span><h2>pyFTS.benchmarks.benchmarks module<a class="headerlink" href="#module-pyFTS.benchmarks.benchmarks" title="Permalink to this headline"></a></h2>
<p>Benchmarks methods for FTS methods</p>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.SelecaoSimples_MenorRMSE">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">SelecaoSimples_MenorRMSE</code><span class="sig-paren">(</span><em>original</em>, <em>parameters</em>, <em>modelo</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#SelecaoSimples_MenorRMSE"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.SelecaoSimples_MenorRMSE" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.compareModelsPlot">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">compareModelsPlot</code><span class="sig-paren">(</span><em>original</em>, <em>models_fo</em>, <em>models_ho</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#compareModelsPlot"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.compareModelsPlot" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.compareModelsTable">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">compareModelsTable</code><span class="sig-paren">(</span><em>original</em>, <em>models_fo</em>, <em>models_ho</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#compareModelsTable"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.compareModelsTable" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.get_benchmark_interval_methods">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">get_benchmark_interval_methods</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#get_benchmark_interval_methods"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.get_benchmark_interval_methods" title="Permalink to this definition"></a></dt>
<dd><p>Return all non FTS methods for point_to_interval forecasting</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.get_benchmark_point_methods">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">get_benchmark_point_methods</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#get_benchmark_point_methods"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.get_benchmark_point_methods" title="Permalink to this definition"></a></dt>
<dd><p>Return all non FTS methods for point forecasting</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.get_benchmark_probabilistic_methods">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">get_benchmark_probabilistic_methods</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#get_benchmark_probabilistic_methods"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.get_benchmark_probabilistic_methods" title="Permalink to this definition"></a></dt>
<dd><p>Return all FTS methods for probabilistic forecasting</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.get_interval_methods">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">get_interval_methods</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#get_interval_methods"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.get_interval_methods" title="Permalink to this definition"></a></dt>
<dd><p>Return all FTS methods for point_to_interval forecasting</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.get_point_methods">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">get_point_methods</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#get_point_methods"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.get_point_methods" title="Permalink to this definition"></a></dt>
<dd><p>Return all FTS methods for point forecasting</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.get_probabilistic_methods">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">get_probabilistic_methods</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#get_probabilistic_methods"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.get_probabilistic_methods" title="Permalink to this definition"></a></dt>
<dd><p>Return all FTS methods for probabilistic forecasting</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.pftsExploreOrderAndPartitions">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">pftsExploreOrderAndPartitions</code><span class="sig-paren">(</span><em>data</em>, <em>save=False</em>, <em>file=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#pftsExploreOrderAndPartitions"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.pftsExploreOrderAndPartitions" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.plotCompared">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plotCompared</code><span class="sig-paren">(</span><em>original</em>, <em>forecasts</em>, <em>labels</em>, <em>title</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plotCompared"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plotCompared" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.plot_compared_intervals_ahead">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_compared_intervals_ahead</code><span class="sig-paren">(</span><em>original, models, colors, distributions, time_from, time_to, intervals=True, save=False, file=None, tam=[20, 5], resolution=None, cmap='Blues', linewidth=1.5</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_compared_intervals_ahead"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_compared_intervals_ahead" title="Permalink to this definition"></a></dt>
<dd><p>Plot the forecasts of several one step ahead models, by point or by interval</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>original</strong> Original time series data (list)</li>
<li><strong>models</strong> List of models to compare</li>
<li><strong>colors</strong> List of models colors</li>
<li><strong>distributions</strong> True to plot a distribution</li>
<li><strong>time_from</strong> index of data poit to start the ahead forecasting</li>
<li><strong>time_to</strong> number of steps ahead to forecast</li>
<li><strong>interpol</strong> Fill space between distribution plots</li>
<li><strong>save</strong> Save the picture on file</li>
<li><strong>file</strong> Filename to save the picture</li>
<li><strong>tam</strong> Size of the picture</li>
<li><strong>resolution</strong> </li>
<li><strong>cmap</strong> Color map to be used on distribution plot</li>
<li><strong>option</strong> Distribution type to be passed for models</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.plot_compared_series">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_compared_series</code><span class="sig-paren">(</span><em>original, models, colors, typeonlegend=False, save=False, file=None, tam=[20, 5], points=True, intervals=True, linewidth=1.5</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_compared_series"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_compared_series" title="Permalink to this definition"></a></dt>
<dd><p>Plot the forecasts of several one step ahead models, by point or by interval</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>original</strong> Original time series data (list)</li>
<li><strong>models</strong> List of models to compare</li>
<li><strong>colors</strong> List of models colors</li>
<li><strong>typeonlegend</strong> Add the type of forecast (point / interval) on legend</li>
<li><strong>save</strong> Save the picture on file</li>
<li><strong>file</strong> Filename to save the picture</li>
<li><strong>tam</strong> Size of the picture</li>
<li><strong>points</strong> True to plot the point forecasts, False otherwise</li>
<li><strong>intervals</strong> True to plot the interval forecasts, False otherwise</li>
<li><strong>linewidth</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.plot_density_rectange">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_density_rectange</code><span class="sig-paren">(</span><em>ax</em>, <em>cmap</em>, <em>density</em>, <em>fig</em>, <em>resolution</em>, <em>time_from</em>, <em>time_to</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_density_rectange"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_density_rectange" title="Permalink to this definition"></a></dt>
<dd><p>Auxiliar function to plot_compared_intervals_ahead</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.plot_distribution">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_distribution</code><span class="sig-paren">(</span><em>ax</em>, <em>cmap</em>, <em>probabilitydist</em>, <em>fig</em>, <em>time_from</em>, <em>reference_data=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_distribution" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.plot_interval">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_interval</code><span class="sig-paren">(</span><em>axis</em>, <em>intervals</em>, <em>order</em>, <em>label</em>, <em>color='red'</em>, <em>typeonlegend=False</em>, <em>ls='-'</em>, <em>linewidth=1</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_interval" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.plot_point">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_point</code><span class="sig-paren">(</span><em>axis</em>, <em>points</em>, <em>order</em>, <em>label</em>, <em>color='red'</em>, <em>ls='-'</em>, <em>linewidth=1</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_point"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_point" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.plot_probability_distributions">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_probability_distributions</code><span class="sig-paren">(</span><em>pmfs, lcolors, tam=[15, 7]</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_probability_distributions"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_probability_distributions" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.print_distribution_statistics">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">print_distribution_statistics</code><span class="sig-paren">(</span><em>original</em>, <em>models</em>, <em>steps</em>, <em>resolution</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#print_distribution_statistics"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.print_distribution_statistics" title="Permalink to this definition"></a></dt>
<dd><p>Run probabilistic benchmarks on given models and data and print the results</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> test data</li>
<li><strong>models</strong> a list of FTS models to benchmark</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.print_interval_statistics">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">print_interval_statistics</code><span class="sig-paren">(</span><em>original</em>, <em>models</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#print_interval_statistics"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.print_interval_statistics" title="Permalink to this definition"></a></dt>
<dd><p>Run interval benchmarks on given models and data and print the results</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> test data</li>
<li><strong>models</strong> a list of FTS models to benchmark</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.print_point_statistics">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">print_point_statistics</code><span class="sig-paren">(</span><em>data</em>, <em>models</em>, <em>externalmodels=None</em>, <em>externalforecasts=None</em>, <em>indexers=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#print_point_statistics"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.print_point_statistics" title="Permalink to this definition"></a></dt>
<dd><p>Run point benchmarks on given models and data and print the results</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> test data</li>
<li><strong>models</strong> a list of FTS models to benchmark</li>
<li><strong>externalmodels</strong> a list with benchmark models (façades for other methods)</li>
<li><strong>externalforecasts</strong> </li>
<li><strong>indexers</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.process_interval_jobs">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">process_interval_jobs</code><span class="sig-paren">(</span><em>dataset</em>, <em>tag</em>, <em>job</em>, <em>conn</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#process_interval_jobs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.process_interval_jobs" title="Permalink to this definition"></a></dt>
<dd><p>Extract information from an dictionary with interval benchmark results and save it on a database</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>dataset</strong> the benchmark dataset name</li>
<li><strong>tag</strong> alias for the benchmark group being executed</li>
<li><strong>job</strong> a dictionary with the benchmark results</li>
<li><strong>conn</strong> a connection to a Sqlite database</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.process_point_jobs">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">process_point_jobs</code><span class="sig-paren">(</span><em>dataset</em>, <em>tag</em>, <em>job</em>, <em>conn</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#process_point_jobs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.process_point_jobs" title="Permalink to this definition"></a></dt>
<dd><p>Extract information from a dictionary with point benchmark results and save it on a database</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>dataset</strong> the benchmark dataset name</li>
<li><strong>tag</strong> alias for the benchmark group being executed</li>
<li><strong>job</strong> a dictionary with the benchmark results</li>
<li><strong>conn</strong> a connection to a Sqlite database</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.process_probabilistic_jobs">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">process_probabilistic_jobs</code><span class="sig-paren">(</span><em>dataset</em>, <em>tag</em>, <em>job</em>, <em>conn</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#process_probabilistic_jobs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.process_probabilistic_jobs" title="Permalink to this definition"></a></dt>
<dd><p>Extract information from an dictionary with probabilistic benchmark results and save it on a database</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>dataset</strong> the benchmark dataset name</li>
<li><strong>tag</strong> alias for the benchmark group being executed</li>
<li><strong>job</strong> a dictionary with the benchmark results</li>
<li><strong>conn</strong> a connection to a Sqlite database</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.run_interval">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">run_interval</code><span class="sig-paren">(</span><em>mfts</em>, <em>partitioner</em>, <em>train_data</em>, <em>test_data</em>, <em>window_key=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#run_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.run_interval" title="Permalink to this definition"></a></dt>
<dd><p>Run the interval forecasting benchmarks</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>mfts</strong> FTS model</li>
<li><strong>partitioner</strong> Universe of Discourse partitioner</li>
<li><strong>train_data</strong> data used to train the model</li>
<li><strong>test_data</strong> ata used to test the model</li>
<li><strong>window_key</strong> id of the sliding window</li>
<li><strong>transformation</strong> data transformation</li>
<li><strong>indexer</strong> seasonal indexer</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a dictionary with the benchmark results</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.run_point">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">run_point</code><span class="sig-paren">(</span><em>mfts</em>, <em>partitioner</em>, <em>train_data</em>, <em>test_data</em>, <em>window_key=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#run_point"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.run_point" title="Permalink to this definition"></a></dt>
<dd><p>Run the point forecasting benchmarks</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>mfts</strong> FTS model</li>
<li><strong>partitioner</strong> Universe of Discourse partitioner</li>
<li><strong>train_data</strong> data used to train the model</li>
<li><strong>test_data</strong> ata used to test the model</li>
<li><strong>window_key</strong> id of the sliding window</li>
<li><strong>transformation</strong> data transformation</li>
<li><strong>indexer</strong> seasonal indexer</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a dictionary with the benchmark results</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.run_probabilistic">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">run_probabilistic</code><span class="sig-paren">(</span><em>mfts</em>, <em>partitioner</em>, <em>train_data</em>, <em>test_data</em>, <em>window_key=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#run_probabilistic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.run_probabilistic" title="Permalink to this definition"></a></dt>
<dd><p>Run the probabilistic forecasting benchmarks</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>mfts</strong> FTS model</li>
<li><strong>partitioner</strong> Universe of Discourse partitioner</li>
<li><strong>train_data</strong> data used to train the model</li>
<li><strong>test_data</strong> ata used to test the model</li>
<li><strong>steps</strong> </li>
<li><strong>resolution</strong> </li>
<li><strong>window_key</strong> id of the sliding window</li>
<li><strong>transformation</strong> data transformation</li>
<li><strong>indexer</strong> seasonal indexer</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a dictionary with the benchmark results</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.simpleSearch_RMSE">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">simpleSearch_RMSE</code><span class="sig-paren">(</span><em>train, test, model, partitions, orders, save=False, file=None, tam=[10, 15], plotforecasts=False, elev=30, azim=144, intervals=False, parameters=None, partitioner=&lt;class 'pyFTS.partitioners.Grid.GridPartitioner'&gt;, transformation=None, indexer=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#simpleSearch_RMSE"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.simpleSearch_RMSE" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.benchmarks.sliding_window_benchmarks">
<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">sliding_window_benchmarks</code><span class="sig-paren">(</span><em>data</em>, <em>windowsize</em>, <em>train=0.8</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#sliding_window_benchmarks"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.sliding_window_benchmarks" title="Permalink to this definition"></a></dt>
<dd><p>Sliding window benchmarks for FTS forecasters.</p>
<p>For each data window, a train and test datasets will be splitted. For each train split, number of
partitions and partitioning method will be created a partitioner model. And for each partitioner, order,
steps ahead and FTS method a foreasting model will be trained.</p>
<p>Then all trained models are benchmarked on the test data and the metrics are stored on a sqlite3 database
(identified by the file parameter) for posterior analysis.</p>
<p>All these process can be distributed on a dispy cluster, setting the atributed distributed to true and
informing the list of dispy nodes on nodes parameter.</p>
<p>The number of experiments is determined by windowsize and inc parameters.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>data</strong> test data</li>
<li><strong>windowsize</strong> size of sliding window</li>
<li><strong>train</strong> percentual of sliding window data used to train the models</li>
<li><strong>kwargs</strong> dict, optional arguments</li>
<li><strong>benchmark_methods</strong> a list with Non FTS models to benchmark. The default is None.</li>
<li><strong>benchmark_methods_parameters</strong> a list with Non FTS models parameters. The default is None.</li>
<li><strong>benchmark_models</strong> A boolean value indicating if external FTS methods will be used on benchmark. The default is False.</li>
<li><strong>build_methods</strong> A boolean value indicating if the default FTS methods will be used on benchmark. The default is True.</li>
<li><strong>dataset</strong> the dataset name to identify the current set of benchmarks results on database.</li>
<li><strong>distributed</strong> A boolean value indicating if the forecasting procedure will be distributed in a dispy cluster. . The default is False</li>
<li><strong>file</strong> file path to save the results. The default is benchmarks.db.</li>
<li><strong>inc</strong> a float on interval [0,1] indicating the percentage of the windowsize to move the window</li>
<li><strong>methods</strong> a list with FTS class names. The default depends on the forecasting type and contains the list of all FTS methods.</li>
<li><strong>models</strong> a list with prebuilt FTS objects. The default is None.</li>
<li><strong>nodes</strong> a list with the dispy cluster nodes addresses. The default is [127.0.0.1].</li>
<li><strong>orders</strong> a list with orders of the models (for high order models). The default is [1,2,3].</li>
<li><strong>partitions</strong> a list with the numbers of partitions on the Universe of Discourse. The default is [10].</li>
<li><strong>partitioners_models</strong> a list with prebuilt Universe of Discourse partitioners objects. The default is None.</li>
<li><strong>partitioners_methods</strong> a list with Universe of Discourse partitioners class names. The default is [partitioners.Grid.GridPartitioner].</li>
<li><strong>progress</strong> If true a progress bar will be displayed during the benchmarks. The default is False.</li>
<li><strong>start</strong> in the multi step forecasting, the index of the data where to start forecasting. The default is 0.</li>
<li><strong>steps_ahead</strong> a list with the forecasting horizons, i. e., the number of steps ahead to forecast. The default is 1.</li>
<li><strong>tag</strong> a name to identify the current set of benchmarks results on database.</li>
<li><strong>type</strong> the forecasting type, one of these values: point(default), interval or distribution. The default is point.</li>
<li><strong>transformations</strong> a list with data transformations do apply . The default is [None].</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.benchmarks.Measures">
<span id="pyfts-benchmarks-measures-module"></span><h2>pyFTS.benchmarks.Measures module<a class="headerlink" href="#module-pyFTS.benchmarks.Measures" title="Permalink to this headline"></a></h2>
<p>pyFTS module for common benchmark metrics</p>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.BoxLjungStatistic">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">BoxLjungStatistic</code><span class="sig-paren">(</span><em>data</em>, <em>h</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#BoxLjungStatistic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.BoxLjungStatistic" title="Permalink to this definition"></a></dt>
<dd><p>Q Statistic for LjungBox test</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> </li>
<li><strong>h</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.BoxPierceStatistic">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">BoxPierceStatistic</code><span class="sig-paren">(</span><em>data</em>, <em>h</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#BoxPierceStatistic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.BoxPierceStatistic" title="Permalink to this definition"></a></dt>
<dd><p>Q Statistic for Box-Pierce test</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> </li>
<li><strong>h</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.TheilsInequality">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">TheilsInequality</code><span class="sig-paren">(</span><em>targets</em>, <em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#TheilsInequality"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.TheilsInequality" title="Permalink to this definition"></a></dt>
<dd><p>Theils Inequality Coefficient</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>targets</strong> </li>
<li><strong>forecasts</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.UStatistic">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">UStatistic</code><span class="sig-paren">(</span><em>targets</em>, <em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#UStatistic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.UStatistic" title="Permalink to this definition"></a></dt>
<dd><p>Theils U Statistic</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>targets</strong> </li>
<li><strong>forecasts</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.acf">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">acf</code><span class="sig-paren">(</span><em>data</em>, <em>k</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#acf"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.acf" title="Permalink to this definition"></a></dt>
<dd><p>Autocorrelation function estimative</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> </li>
<li><strong>k</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.brier_score">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">brier_score</code><span class="sig-paren">(</span><em>targets</em>, <em>densities</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#brier_score"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.brier_score" title="Permalink to this definition"></a></dt>
<dd><p>Brier (1950). “Verification of Forecasts Expressed in Terms of Probability”. Monthly Weather Review. 78: 13.</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.coverage">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">coverage</code><span class="sig-paren">(</span><em>targets</em>, <em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#coverage"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.coverage" title="Permalink to this definition"></a></dt>
<dd><p>Percent of target values that fall inside forecasted interval</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.crps">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">crps</code><span class="sig-paren">(</span><em>targets</em>, <em>densities</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#crps"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.crps" title="Permalink to this definition"></a></dt>
<dd><p>Continuous Ranked Probability Score</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>targets</strong> a list with the target values</li>
<li><strong>densities</strong> a list with pyFTS.probabil objectsistic.ProbabilityDistribution</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">float</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.get_distribution_statistics">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">get_distribution_statistics</code><span class="sig-paren">(</span><em>data</em>, <em>model</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#get_distribution_statistics"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.get_distribution_statistics" title="Permalink to this definition"></a></dt>
<dd><p>Get CRPS statistic and time for a forecasting model</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> test data</li>
<li><strong>model</strong> FTS model with probabilistic forecasting capability</li>
<li><strong>kwargs</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the CRPS and execution time</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.get_interval_statistics">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">get_interval_statistics</code><span class="sig-paren">(</span><em>data</em>, <em>model</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#get_interval_statistics"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.get_interval_statistics" title="Permalink to this definition"></a></dt>
<dd><p>Condensate all measures for point interval forecasters</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> test data</li>
<li><strong>model</strong> FTS model with interval forecasting capability</li>
<li><strong>kwargs</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the sharpness, resolution, coverage, .05 pinball mean,</p>
</td>
</tr>
</tbody>
</table>
<p>.25 pinball mean, .75 pinball mean and .95 pinball mean.</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.get_point_statistics">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">get_point_statistics</code><span class="sig-paren">(</span><em>data</em>, <em>model</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#get_point_statistics"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.get_point_statistics" title="Permalink to this definition"></a></dt>
<dd><p>Condensate all measures for point forecasters</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> test data</li>
<li><strong>model</strong> FTS model with point forecasting capability</li>
<li><strong>kwargs</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the RMSE, SMAPE and U Statistic</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.heavyside">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">heavyside</code><span class="sig-paren">(</span><em>bin</em>, <em>target</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#heavyside"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.heavyside" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.heavyside_cdf">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">heavyside_cdf</code><span class="sig-paren">(</span><em>bins</em>, <em>targets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#heavyside_cdf"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.heavyside_cdf" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.mape">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">mape</code><span class="sig-paren">(</span><em>targets</em>, <em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#mape"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.mape" title="Permalink to this definition"></a></dt>
<dd><p>Mean Average Percentual Error</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>targets</strong> </li>
<li><strong>forecasts</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.mape_interval">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">mape_interval</code><span class="sig-paren">(</span><em>targets</em>, <em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#mape_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.mape_interval" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.pinball">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">pinball</code><span class="sig-paren">(</span><em>tau</em>, <em>target</em>, <em>forecast</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#pinball"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.pinball" title="Permalink to this definition"></a></dt>
<dd><p>Pinball loss function. Measure the distance of forecast to the tau-quantile of the target</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>tau</strong> quantile value in the range (0,1)</li>
<li><strong>target</strong> </li>
<li><strong>forecast</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">float, distance of forecast to the tau-quantile of the target</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.pinball_mean">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">pinball_mean</code><span class="sig-paren">(</span><em>tau</em>, <em>targets</em>, <em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#pinball_mean"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.pinball_mean" title="Permalink to this definition"></a></dt>
<dd><p>Mean pinball loss value of the forecast for a given tau-quantile of the targets</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>tau</strong> quantile value in the range (0,1)</li>
<li><strong>targets</strong> list of target values</li>
<li><strong>forecasts</strong> list of prediction intervals</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">float, the pinball loss mean for tau quantile</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.pmf_to_cdf">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">pmf_to_cdf</code><span class="sig-paren">(</span><em>density</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#pmf_to_cdf"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.pmf_to_cdf" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.resolution">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">resolution</code><span class="sig-paren">(</span><em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#resolution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.resolution" title="Permalink to this definition"></a></dt>
<dd><p>Resolution - Standard deviation of the intervals</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.rmse">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">rmse</code><span class="sig-paren">(</span><em>targets</em>, <em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#rmse"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.rmse" title="Permalink to this definition"></a></dt>
<dd><p>Root Mean Squared Error</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>targets</strong> </li>
<li><strong>forecasts</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.rmse_interval">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">rmse_interval</code><span class="sig-paren">(</span><em>targets</em>, <em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#rmse_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.rmse_interval" title="Permalink to this definition"></a></dt>
<dd><p>Root Mean Squared Error</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>targets</strong> </li>
<li><strong>forecasts</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.sharpness">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">sharpness</code><span class="sig-paren">(</span><em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#sharpness"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.sharpness" title="Permalink to this definition"></a></dt>
<dd><p>Sharpness - Mean size of the intervals</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.smape">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">smape</code><span class="sig-paren">(</span><em>targets</em>, <em>forecasts</em>, <em>type=2</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#smape"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.smape" title="Permalink to this definition"></a></dt>
<dd><p>Symmetric Mean Average Percentual Error</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>targets</strong> </li>
<li><strong>forecasts</strong> </li>
<li><strong>type</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.winkler_mean">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">winkler_mean</code><span class="sig-paren">(</span><em>tau</em>, <em>targets</em>, <em>forecasts</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#winkler_mean"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.winkler_mean" title="Permalink to this definition"></a></dt>
<dd><p>Mean Winkler score value of the forecast for a given tau-quantile of the targets</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>tau</strong> quantile value in the range (0,1)</li>
<li><strong>targets</strong> list of target values</li>
<li><strong>forecasts</strong> list of prediction intervals</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">float, the Winkler score mean for tau quantile</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Measures.winkler_score">
<code class="descclassname">pyFTS.benchmarks.Measures.</code><code class="descname">winkler_score</code><span class="sig-paren">(</span><em>tau</em>, <em>target</em>, <em>forecast</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Measures.html#winkler_score"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Measures.winkler_score" title="Permalink to this definition"></a></dt>
<dd><ol class="upperalpha simple" start="18">
<li><ol class="first upperalpha" start="12">
<li>Winkler, A Decision-Theoretic Approach to Interval Estimation, J. Am. Stat. Assoc. 67 (337) (1972) 187191. doi:10.2307/2284720.</li>
</ol>
</li>
</ol>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.benchmarks.ResidualAnalysis">
<span id="pyfts-benchmarks-residualanalysis-module"></span><h2>pyFTS.benchmarks.ResidualAnalysis module<a class="headerlink" href="#module-pyFTS.benchmarks.ResidualAnalysis" title="Permalink to this headline"></a></h2>
<p>Residual Analysis methods</p>
<dl class="function">
<dt id="pyFTS.benchmarks.ResidualAnalysis.chi_squared">
<code class="descclassname">pyFTS.benchmarks.ResidualAnalysis.</code><code class="descname">chi_squared</code><span class="sig-paren">(</span><em>q</em>, <em>h</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/ResidualAnalysis.html#chi_squared"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.ResidualAnalysis.chi_squared" title="Permalink to this definition"></a></dt>
<dd><p>Chi-Squared value</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>q</strong> </li>
<li><strong>h</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.ResidualAnalysis.compare_residuals">
<code class="descclassname">pyFTS.benchmarks.ResidualAnalysis.</code><code class="descname">compare_residuals</code><span class="sig-paren">(</span><em>data</em>, <em>models</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/ResidualAnalysis.html#compare_residuals"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.ResidualAnalysis.compare_residuals" title="Permalink to this definition"></a></dt>
<dd><p>Compare residuals statistics of several models</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> test data</li>
<li><strong>models</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a Pandas dataframe with the Box-Ljung statistic for each model</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.ResidualAnalysis.plotResiduals">
<code class="descclassname">pyFTS.benchmarks.ResidualAnalysis.</code><code class="descname">plotResiduals</code><span class="sig-paren">(</span><em>targets, models, tam=[8, 8], save=False, file=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/ResidualAnalysis.html#plotResiduals"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.ResidualAnalysis.plotResiduals" title="Permalink to this definition"></a></dt>
<dd><p>Plot residuals and statistics</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>targets</strong> </li>
<li><strong>models</strong> </li>
<li><strong>tam</strong> </li>
<li><strong>save</strong> </li>
<li><strong>file</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.ResidualAnalysis.plot_residuals">
<code class="descclassname">pyFTS.benchmarks.ResidualAnalysis.</code><code class="descname">plot_residuals</code><span class="sig-paren">(</span><em>targets, models, tam=[8, 8], save=False, file=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/ResidualAnalysis.html#plot_residuals"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.ResidualAnalysis.plot_residuals" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.ResidualAnalysis.residuals">
<code class="descclassname">pyFTS.benchmarks.ResidualAnalysis.</code><code class="descname">residuals</code><span class="sig-paren">(</span><em>targets</em>, <em>forecasts</em>, <em>order=1</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/ResidualAnalysis.html#residuals"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.ResidualAnalysis.residuals" title="Permalink to this definition"></a></dt>
<dd><p>First order residuals</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.ResidualAnalysis.single_plot_residuals">
<code class="descclassname">pyFTS.benchmarks.ResidualAnalysis.</code><code class="descname">single_plot_residuals</code><span class="sig-paren">(</span><em>targets, forecasts, order, tam=[8, 8], save=False, file=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/ResidualAnalysis.html#single_plot_residuals"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.ResidualAnalysis.single_plot_residuals" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</div>
<div class="section" id="module-pyFTS.benchmarks.Util">
<span id="pyfts-benchmarks-util-module"></span><h2>pyFTS.benchmarks.Util module<a class="headerlink" href="#module-pyFTS.benchmarks.Util" title="Permalink to this headline"></a></h2>
<p>Facilities for pyFTS Benchmark module</p>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.analytic_tabular_dataframe">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">analytic_tabular_dataframe</code><span class="sig-paren">(</span><em>dataframe</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#analytic_tabular_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.analytic_tabular_dataframe" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.analytical_data_columns">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">analytical_data_columns</code><span class="sig-paren">(</span><em>experiments</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#analytical_data_columns"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.analytical_data_columns" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.base_dataframe_columns">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">base_dataframe_columns</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#base_dataframe_columns"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.base_dataframe_columns" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.cast_dataframe_to_synthetic">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">cast_dataframe_to_synthetic</code><span class="sig-paren">(</span><em>infile</em>, <em>outfile</em>, <em>experiments</em>, <em>type</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#cast_dataframe_to_synthetic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.cast_dataframe_to_synthetic" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.cast_dataframe_to_synthetic_interval">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">cast_dataframe_to_synthetic_interval</code><span class="sig-paren">(</span><em>df</em>, <em>data_columns</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#cast_dataframe_to_synthetic_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.cast_dataframe_to_synthetic_interval" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.cast_dataframe_to_synthetic_point">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">cast_dataframe_to_synthetic_point</code><span class="sig-paren">(</span><em>df</em>, <em>data_columns</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#cast_dataframe_to_synthetic_point"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.cast_dataframe_to_synthetic_point" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.cast_dataframe_to_synthetic_probabilistic">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">cast_dataframe_to_synthetic_probabilistic</code><span class="sig-paren">(</span><em>df</em>, <em>data_columns</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#cast_dataframe_to_synthetic_probabilistic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.cast_dataframe_to_synthetic_probabilistic" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.check_ignore_list">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">check_ignore_list</code><span class="sig-paren">(</span><em>b</em>, <em>ignore</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#check_ignore_list"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.check_ignore_list" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.check_replace_list">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">check_replace_list</code><span class="sig-paren">(</span><em>m</em>, <em>replace</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#check_replace_list"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.check_replace_list" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.create_benchmark_tables">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">create_benchmark_tables</code><span class="sig-paren">(</span><em>conn</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#create_benchmark_tables"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.create_benchmark_tables" title="Permalink to this definition"></a></dt>
<dd><p>Create a sqlite3 table designed to store benchmark results.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>conn</strong> a sqlite3 database connection</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.extract_measure">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">extract_measure</code><span class="sig-paren">(</span><em>dataframe</em>, <em>measure</em>, <em>data_columns</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#extract_measure"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.extract_measure" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.find_best">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">find_best</code><span class="sig-paren">(</span><em>dataframe</em>, <em>criteria</em>, <em>ascending</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#find_best"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.find_best" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.get_dataframe_from_bd">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">get_dataframe_from_bd</code><span class="sig-paren">(</span><em>file</em>, <em>filter</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#get_dataframe_from_bd"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.get_dataframe_from_bd" title="Permalink to this definition"></a></dt>
<dd><p>Query the sqlite benchmark database and return a pandas dataframe with the results</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>file</strong> the url of the benchmark database</li>
<li><strong>filter</strong> sql conditions to filter</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">pandas dataframe with the query results</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.insert_benchmark">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">insert_benchmark</code><span class="sig-paren">(</span><em>data</em>, <em>conn</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#insert_benchmark"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.insert_benchmark" title="Permalink to this definition"></a></dt>
<dd><p>Insert benchmark data on database</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>data</strong> a tuple with the benchmark data with format:</td>
</tr>
</tbody>
</table>
<p>ID: integer incremental primary key
Date: Date/hour of benchmark execution
Dataset: Identify on which dataset the dataset was performed
Tag: a user defined word that indentify a benchmark set
Type: forecasting type (point, interval, distribution)
Model: FTS model
Transformation: The name of data transformation, if one was used
Order: the order of the FTS method
Scheme: UoD partitioning scheme
Partitions: Number of partitions
Size: Number of rules of the FTS model
Steps: prediction horizon, i. e., the number of steps ahead
Measure: accuracy measure
Value: the measure value</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>conn</strong> a sqlite3 database connection</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.interval_dataframe_analytic_columns">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">interval_dataframe_analytic_columns</code><span class="sig-paren">(</span><em>experiments</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#interval_dataframe_analytic_columns"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.interval_dataframe_analytic_columns" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.interval_dataframe_synthetic_columns">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">interval_dataframe_synthetic_columns</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#interval_dataframe_synthetic_columns"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.interval_dataframe_synthetic_columns" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.open_benchmark_db">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">open_benchmark_db</code><span class="sig-paren">(</span><em>name</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#open_benchmark_db"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.open_benchmark_db" title="Permalink to this definition"></a></dt>
<dd><p>Open a connection with a Sqlite database designed to store benchmark results.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>name</strong> database filenem</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">a sqlite3 database connection</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.plot_dataframe_interval">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">plot_dataframe_interval</code><span class="sig-paren">(</span><em>file_synthetic, file_analytic, experiments, tam, save=False, file=None, sort_columns=['COVAVG', 'SHARPAVG', 'COVSTD', 'SHARPSTD'], sort_ascend=[True, False, True, True], save_best=False, ignore=None, replace=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#plot_dataframe_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.plot_dataframe_interval" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.plot_dataframe_interval_pinball">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">plot_dataframe_interval_pinball</code><span class="sig-paren">(</span><em>file_synthetic, file_analytic, experiments, tam, save=False, file=None, sort_columns=['COVAVG', 'SHARPAVG', 'COVSTD', 'SHARPSTD'], sort_ascend=[True, False, True, True], save_best=False, ignore=None, replace=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#plot_dataframe_interval_pinball"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.plot_dataframe_interval_pinball" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.plot_dataframe_point">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">plot_dataframe_point</code><span class="sig-paren">(</span><em>file_synthetic, file_analytic, experiments, tam, save=False, file=None, sort_columns=['UAVG', 'RMSEAVG', 'USTD', 'RMSESTD'], sort_ascend=[1, 1, 1, 1], save_best=False, ignore=None, replace=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#plot_dataframe_point"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.plot_dataframe_point" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.plot_dataframe_probabilistic">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">plot_dataframe_probabilistic</code><span class="sig-paren">(</span><em>file_synthetic, file_analytic, experiments, tam, save=False, file=None, sort_columns=['CRPS1AVG', 'CRPS2AVG', 'CRPS1STD', 'CRPS2STD'], sort_ascend=[True, True, True, True], save_best=False, ignore=None, replace=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#plot_dataframe_probabilistic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.plot_dataframe_probabilistic" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.point_dataframe_analytic_columns">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">point_dataframe_analytic_columns</code><span class="sig-paren">(</span><em>experiments</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#point_dataframe_analytic_columns"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.point_dataframe_analytic_columns" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.point_dataframe_synthetic_columns">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">point_dataframe_synthetic_columns</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#point_dataframe_synthetic_columns"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.point_dataframe_synthetic_columns" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.probabilistic_dataframe_analytic_columns">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">probabilistic_dataframe_analytic_columns</code><span class="sig-paren">(</span><em>experiments</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#probabilistic_dataframe_analytic_columns"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.probabilistic_dataframe_analytic_columns" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.probabilistic_dataframe_synthetic_columns">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">probabilistic_dataframe_synthetic_columns</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#probabilistic_dataframe_synthetic_columns"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.probabilistic_dataframe_synthetic_columns" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.process_common_data">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">process_common_data</code><span class="sig-paren">(</span><em>dataset</em>, <em>tag</em>, <em>type</em>, <em>job</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#process_common_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.process_common_data" title="Permalink to this definition"></a></dt>
<dd><p>Wraps benchmark information on a tuple for sqlite database</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>dataset</strong> benchmark dataset</li>
<li><strong>tag</strong> benchmark set alias</li>
<li><strong>type</strong> forecasting type</li>
<li><strong>job</strong> a dictionary with benchmark data</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">tuple for sqlite database</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.save_dataframe_interval">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">save_dataframe_interval</code><span class="sig-paren">(</span><em>coverage</em>, <em>experiments</em>, <em>file</em>, <em>objs</em>, <em>resolution</em>, <em>save</em>, <em>sharpness</em>, <em>synthetic</em>, <em>times</em>, <em>q05</em>, <em>q25</em>, <em>q75</em>, <em>q95</em>, <em>steps</em>, <em>method</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#save_dataframe_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.save_dataframe_interval" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.save_dataframe_point">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">save_dataframe_point</code><span class="sig-paren">(</span><em>experiments</em>, <em>file</em>, <em>objs</em>, <em>rmse</em>, <em>save</em>, <em>synthetic</em>, <em>smape</em>, <em>times</em>, <em>u</em>, <em>steps</em>, <em>method</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#save_dataframe_point"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.save_dataframe_point" title="Permalink to this definition"></a></dt>
<dd><p>Create a dataframe to store the benchmark results</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>experiments</strong> dictionary with the execution results</li>
<li><strong>file</strong> </li>
<li><strong>objs</strong> </li>
<li><strong>rmse</strong> </li>
<li><strong>save</strong> </li>
<li><strong>synthetic</strong> </li>
<li><strong>smape</strong> </li>
<li><strong>times</strong> </li>
<li><strong>u</strong> </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.save_dataframe_probabilistic">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">save_dataframe_probabilistic</code><span class="sig-paren">(</span><em>experiments</em>, <em>file</em>, <em>objs</em>, <em>crps</em>, <em>times</em>, <em>save</em>, <em>synthetic</em>, <em>steps</em>, <em>method</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#save_dataframe_probabilistic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.save_dataframe_probabilistic" title="Permalink to this definition"></a></dt>
<dd><p>Save benchmark results for m-step ahead probabilistic forecasters
:param experiments:
:param file:
:param objs:
:param crps_interval:
:param crps_distr:
:param times:
:param times2:
:param save:
:param synthetic:
:return:</p>
</dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.scale">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">scale</code><span class="sig-paren">(</span><em>data</em>, <em>params</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#scale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.scale" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.scale_params">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">scale_params</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#scale_params"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.scale_params" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.stats">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">stats</code><span class="sig-paren">(</span><em>measure</em>, <em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#stats"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.stats" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.tabular_dataframe_columns">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">tabular_dataframe_columns</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#tabular_dataframe_columns"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.tabular_dataframe_columns" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.unified_scaled_interval">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">unified_scaled_interval</code><span class="sig-paren">(</span><em>experiments, tam, save=False, file=None, sort_columns=['COVAVG', 'SHARPAVG', 'COVSTD', 'SHARPSTD'], sort_ascend=[True, False, True, True], save_best=False, ignore=None, replace=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#unified_scaled_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.unified_scaled_interval" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.unified_scaled_interval_pinball">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">unified_scaled_interval_pinball</code><span class="sig-paren">(</span><em>experiments, tam, save=False, file=None, sort_columns=['COVAVG', 'SHARPAVG', 'COVSTD', 'SHARPSTD'], sort_ascend=[True, False, True, True], save_best=False, ignore=None, replace=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#unified_scaled_interval_pinball"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.unified_scaled_interval_pinball" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.unified_scaled_point">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">unified_scaled_point</code><span class="sig-paren">(</span><em>experiments, tam, save=False, file=None, sort_columns=['UAVG', 'RMSEAVG', 'USTD', 'RMSESTD'], sort_ascend=[1, 1, 1, 1], save_best=False, ignore=None, replace=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#unified_scaled_point"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.unified_scaled_point" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="function">
<dt id="pyFTS.benchmarks.Util.unified_scaled_probabilistic">
<code class="descclassname">pyFTS.benchmarks.Util.</code><code class="descname">unified_scaled_probabilistic</code><span class="sig-paren">(</span><em>experiments, tam, save=False, file=None, sort_columns=['CRPSAVG', 'CRPSSTD'], sort_ascend=[True, True], save_best=False, ignore=None, replace=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/Util.html#unified_scaled_probabilistic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.Util.unified_scaled_probabilistic" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</div>
<div class="section" id="module-pyFTS.benchmarks.arima">
<span id="pyfts-benchmarks-arima-module"></span><h2>pyFTS.benchmarks.arima module<a class="headerlink" href="#module-pyFTS.benchmarks.arima" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.benchmarks.arima.ARIMA">
<em class="property">class </em><code class="descclassname">pyFTS.benchmarks.arima.</code><code class="descname">ARIMA</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/arima.html#ARIMA"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.arima.ARIMA" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>Façade for statsmodels.tsa.arima_model</p>
<dl class="method">
<dt id="pyFTS.benchmarks.arima.ARIMA.ar">
<code class="descname">ar</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/arima.html#ARIMA.ar"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.arima.ARIMA.ar" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.arima.ARIMA.forecast">
<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/arima.html#ARIMA.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.arima.ARIMA.forecast" title="Permalink to this definition"></a></dt>
<dd><p>Point forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted values</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.arima.ARIMA.forecast_ahead_distribution">
<code class="descname">forecast_ahead_distribution</code><span class="sig-paren">(</span><em>data</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/arima.html#ARIMA.forecast_ahead_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.arima.ARIMA.forecast_ahead_distribution" title="Permalink to this definition"></a></dt>
<dd><p>Probabilistic forecast n steps ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>steps</strong> the number of steps ahead to forecast</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted Probability Distributions</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.arima.ARIMA.forecast_ahead_interval">
<code class="descname">forecast_ahead_interval</code><span class="sig-paren">(</span><em>ndata</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/arima.html#ARIMA.forecast_ahead_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.arima.ARIMA.forecast_ahead_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast n steps ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>steps</strong> the number of steps ahead to forecast</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted intervals</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.arima.ARIMA.forecast_distribution">
<code class="descname">forecast_distribution</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/arima.html#ARIMA.forecast_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.arima.ARIMA.forecast_distribution" title="Permalink to this definition"></a></dt>
<dd><p>Probabilistic forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted Probability Distributions</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.arima.ARIMA.forecast_interval">
<code class="descname">forecast_interval</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/arima.html#ARIMA.forecast_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.arima.ARIMA.forecast_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted intervals</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.arima.ARIMA.ma">
<code class="descname">ma</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/arima.html#ARIMA.ma"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.arima.ARIMA.ma" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.arima.ARIMA.train">
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/arima.html#ARIMA.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.arima.ARIMA.train" title="Permalink to this definition"></a></dt>
<dd><p>Method specific parameter fitting</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>data</strong> training time series data</li>
<li><strong>kwargs</strong> Method specific parameters</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.benchmarks.knn">
<span id="pyfts-benchmarks-knn-module"></span><h2>pyFTS.benchmarks.knn module<a class="headerlink" href="#module-pyFTS.benchmarks.knn" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.benchmarks.knn.KNearestNeighbors">
<em class="property">class </em><code class="descclassname">pyFTS.benchmarks.knn.</code><code class="descname">KNearestNeighbors</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/knn.html#KNearestNeighbors"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.knn.KNearestNeighbors" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>K-Nearest Neighbors</p>
<dl class="method">
<dt id="pyFTS.benchmarks.knn.KNearestNeighbors.forecast_distribution">
<code class="descname">forecast_distribution</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/knn.html#KNearestNeighbors.forecast_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.knn.KNearestNeighbors.forecast_distribution" title="Permalink to this definition"></a></dt>
<dd><p>Probabilistic forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted Probability Distributions</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.knn.KNearestNeighbors.knn">
<code class="descname">knn</code><span class="sig-paren">(</span><em>sample</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/knn.html#KNearestNeighbors.knn"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.knn.KNearestNeighbors.knn" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.knn.KNearestNeighbors.train">
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/knn.html#KNearestNeighbors.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.knn.KNearestNeighbors.train" title="Permalink to this definition"></a></dt>
<dd><p>Method specific parameter fitting</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>data</strong> training time series data</li>
<li><strong>kwargs</strong> Method specific parameters</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.benchmarks.naive">
<span id="pyfts-benchmarks-naive-module"></span><h2>pyFTS.benchmarks.naive module<a class="headerlink" href="#module-pyFTS.benchmarks.naive" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.benchmarks.naive.Naive">
<em class="property">class </em><code class="descclassname">pyFTS.benchmarks.naive.</code><code class="descname">Naive</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/naive.html#Naive"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.naive.Naive" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>Naïve Forecasting method</p>
<dl class="method">
<dt id="pyFTS.benchmarks.naive.Naive.forecast">
<code class="descname">forecast</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/naive.html#Naive.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.naive.Naive.forecast" title="Permalink to this definition"></a></dt>
<dd><p>Point forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted values</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.benchmarks.quantreg">
<span id="pyfts-benchmarks-quantreg-module"></span><h2>pyFTS.benchmarks.quantreg module<a class="headerlink" href="#module-pyFTS.benchmarks.quantreg" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression">
<em class="property">class </em><code class="descclassname">pyFTS.benchmarks.quantreg.</code><code class="descname">QuantileRegression</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>Façade for statsmodels.regression.quantile_regression</p>
<dl class="method">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression.forecast">
<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression.forecast" title="Permalink to this definition"></a></dt>
<dd><p>Point forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted values</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression.forecast_ahead_distribution">
<code class="descname">forecast_ahead_distribution</code><span class="sig-paren">(</span><em>ndata</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression.forecast_ahead_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression.forecast_ahead_distribution" title="Permalink to this definition"></a></dt>
<dd><p>Probabilistic forecast n steps ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>steps</strong> the number of steps ahead to forecast</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted Probability Distributions</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression.forecast_ahead_interval">
<code class="descname">forecast_ahead_interval</code><span class="sig-paren">(</span><em>ndata</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression.forecast_ahead_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression.forecast_ahead_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast n steps ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>steps</strong> the number of steps ahead to forecast</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted intervals</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression.forecast_distribution">
<code class="descname">forecast_distribution</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression.forecast_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression.forecast_distribution" title="Permalink to this definition"></a></dt>
<dd><p>Probabilistic forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted Probability Distributions</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression.forecast_interval">
<code class="descname">forecast_interval</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression.forecast_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression.forecast_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted intervals</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression.interval_to_interval">
<code class="descname">interval_to_interval</code><span class="sig-paren">(</span><em>data</em>, <em>lo_params</em>, <em>up_params</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression.interval_to_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression.interval_to_interval" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression.linearmodel">
<code class="descname">linearmodel</code><span class="sig-paren">(</span><em>data</em>, <em>params</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression.linearmodel"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression.linearmodel" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression.point_to_interval">
<code class="descname">point_to_interval</code><span class="sig-paren">(</span><em>data</em>, <em>lo_params</em>, <em>up_params</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression.point_to_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression.point_to_interval" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.benchmarks.quantreg.QuantileRegression.train">
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/quantreg.html#QuantileRegression.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.quantreg.QuantileRegression.train" title="Permalink to this definition"></a></dt>
<dd><p>Method specific parameter fitting</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>data</strong> training time series data</li>
<li><strong>kwargs</strong> Method specific parameters</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
</div>
</div>
</div>
</div>
<div class="clearer"></div>
</div>
<div class="related" role="navigation" aria-label="related navigation">
<h3>Navigation</h3>
<ul>
<li class="right" style="margin-right: 10px">
<a href="genindex.html" title="General Index"
>index</a></li>
<li class="right" >
<a href="py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="right" >
<a href="pyFTS.common.html" title="pyFTS.common package"
>next</a> |</li>
<li class="right" >
<a href="pyFTS.html" title="pyFTS package"
>previous</a> |</li>
<li class="nav-item nav-item-0"><a href="index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="modules.html" >pyFTS</a> &#187;</li>
<li class="nav-item nav-item-2"><a href="pyFTS.html" >pyFTS package</a> &#187;</li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.7.2.
</div>
</body>
</html>