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<title>pyFTS.probabilistic package &#8212; pyFTS 1.2.3 documentation</title>
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<div class="section" id="pyfts-probabilistic-package">
<h1>pyFTS.probabilistic package<a class="headerlink" href="#pyfts-probabilistic-package" title="Permalink to this headline"></a></h1>
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<div class="section" id="module-pyFTS.probabilistic">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.probabilistic" title="Permalink to this headline"></a></h2>
<p>Probability Distribution objects</p>
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<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
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<div class="section" id="module-pyFTS.probabilistic.ProbabilityDistribution">
<span id="pyfts-probabilistic-probabilitydistribution-module"></span><h2>pyFTS.probabilistic.ProbabilityDistribution module<a class="headerlink" href="#module-pyFTS.probabilistic.ProbabilityDistribution" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution">
<em class="property">class </em><code class="descclassname">pyFTS.probabilistic.ProbabilityDistribution.</code><code class="descname">ProbabilityDistribution</code><span class="sig-paren">(</span><em>type='KDE'</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
<p>Represents a discrete or continous probability distribution
If type is histogram, the PDF is discrete
If type is KDE the PDF is continuous</p>
<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.append">
<code class="descname">append</code><span class="sig-paren">(</span><em>values</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.append"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.append" title="Permalink to this definition"></a></dt>
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<dd><p>Increment the frequency count for the values</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>values</strong> – A list of values to account the frequency</td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.append_interval">
<code class="descname">append_interval</code><span class="sig-paren">(</span><em>intervals</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.append_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.append_interval" title="Permalink to this definition"></a></dt>
Improving documentation for the Interval and Probabilistic forecasts
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<dd><p>Increment the frequency count for all values inside an 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"><strong>intervals</strong> – A list of intervals do increment the frequency</td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.averageloglikelihood">
<code class="descname">averageloglikelihood</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.averageloglikelihood"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.averageloglikelihood" title="Permalink to this definition"></a></dt>
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<dd><p>Average log likelihood of the probability distribution with respect to data</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> – </td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="attribute">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.bins">
<code class="descname">bins</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.bins" title="Permalink to this definition"></a></dt>
<dd><p>Number of bins on a discrete PDF</p>
</dd></dl>
<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.build_cdf_qtl">
<code class="descname">build_cdf_qtl</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.build_cdf_qtl"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.build_cdf_qtl" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.crossentropy">
<code class="descname">crossentropy</code><span class="sig-paren">(</span><em>q</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.crossentropy"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.crossentropy" title="Permalink to this definition"></a></dt>
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<dd><p>Cross entropy between the actual probability distribution and the informed one.</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>q</strong> – a probabilistic.ProbabilityDistribution object</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">Cross entropy between this probability distribution and the given distribution</td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
Improving documentation for the Interval and Probabilistic forecasts
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<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.cumulative">
<code class="descname">cumulative</code><span class="sig-paren">(</span><em>values</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.cumulative"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.cumulative" title="Permalink to this definition"></a></dt>
<dd><p>Return the cumulative probability densities for the input values</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>values</strong> – A list of input values</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">The cumulative probability densities for the input values</td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.density">
<code class="descname">density</code><span class="sig-paren">(</span><em>values</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.density"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.density" title="Permalink to this definition"></a></dt>
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<dd><p>Return the probability densities for the input values</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>values</strong> – List of values to return the densities</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">List of probability densities for the input values</td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.differential_offset">
<code class="descname">differential_offset</code><span class="sig-paren">(</span><em>value</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.differential_offset"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.differential_offset" title="Permalink to this definition"></a></dt>
Improving documentation for the Interval and Probabilistic forecasts
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<dd><p>Auxiliary function for probability distributions of differentiated data</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>value</strong> – </td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.empiricalloglikelihood">
<code class="descname">empiricalloglikelihood</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.empiricalloglikelihood"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.empiricalloglikelihood" title="Permalink to this definition"></a></dt>
Improving documentation for the Interval and Probabilistic forecasts
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<dd><p>Empirical Log Likelihood of the probability distribution</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">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.entropy">
<code class="descname">entropy</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.entropy"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.entropy" title="Permalink to this definition"></a></dt>
Improving documentation for the Interval and Probabilistic forecasts
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<dd><p>Return the entropy of the probability distribution, H[X] =</p>
<p>:return:the entropy of the probability distribution</p>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.expected_value">
<code class="descname">expected_value</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.expected_value"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.expected_value" title="Permalink to this definition"></a></dt>
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<dd><p>Return the expected value of the distribution, as E[X] = ∑ x * P(x)</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">Returns:</th><td class="field-body">The expected value of the distribution</td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.kullbackleiblerdivergence">
<code class="descname">kullbackleiblerdivergence</code><span class="sig-paren">(</span><em>q</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.kullbackleiblerdivergence"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.kullbackleiblerdivergence" title="Permalink to this definition"></a></dt>
Improving documentation for the Interval and Probabilistic forecasts
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<dd><p>Kullback-Leibler divergence between the actual probability distribution and the informed one.</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>q</strong> – a probabilistic.ProbabilityDistribution object</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">Kullback-Leibler divergence</td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="attribute">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.labels">
<code class="descname">labels</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.labels" title="Permalink to this definition"></a></dt>
<dd><p>Bins labels on a discrete PDF</p>
</dd></dl>
<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.plot">
<code class="descname">plot</code><span class="sig-paren">(</span><em>axis=None, color='black', tam=[10, 6], title=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.plot"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.plot" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.pseudologlikelihood">
<code class="descname">pseudologlikelihood</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.pseudologlikelihood"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.pseudologlikelihood" title="Permalink to this definition"></a></dt>
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<dd><p>Pseudo log likelihood of the probability distribution with respect to data</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> – </td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.quantile">
<code class="descname">quantile</code><span class="sig-paren">(</span><em>values</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.quantile"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.quantile" title="Permalink to this definition"></a></dt>
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<dd><p>Return the quantile values for the input values</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>values</strong> – input values</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">The list of the quantile values for the input values</td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="method">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.set">
<code class="descname">set</code><span class="sig-paren">(</span><em>value</em>, <em>density</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/ProbabilityDistribution.html#ProbabilityDistribution.set"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.set" title="Permalink to this definition"></a></dt>
Improving documentation for the Interval and Probabilistic forecasts
2018-09-29 02:35:07 +04:00
<dd><p>Assert a probability ‘density’ for a certain value ‘value’, such that P(value) = density</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>value</strong> – A value in the universe of discourse from the distribution</li>
<li><strong>density</strong> – The probability density to assign to the value</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
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<dl class="attribute">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.type">
<code class="descname">type</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.type" title="Permalink to this definition"></a></dt>
<dd><p>If type is histogram, the PDF is discrete
If type is KDE the PDF is continuous</p>
</dd></dl>
<dl class="attribute">
<dt id="pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.uod">
<code class="descname">uod</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.uod" title="Permalink to this definition"></a></dt>
<dd><p>Universe of discourse</p>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.probabilistic.kde">
<span id="pyfts-probabilistic-kde-module"></span><h2>pyFTS.probabilistic.kde module<a class="headerlink" href="#module-pyFTS.probabilistic.kde" title="Permalink to this headline"></a></h2>
<p>Kernel Density Estimation</p>
<dl class="class">
<dt id="pyFTS.probabilistic.kde.KernelSmoothing">
<em class="property">class </em><code class="descclassname">pyFTS.probabilistic.kde.</code><code class="descname">KernelSmoothing</code><span class="sig-paren">(</span><em>h</em>, <em>kernel='epanechnikov'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/kde.html#KernelSmoothing"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.kde.KernelSmoothing" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
<p>Kernel Density Estimation</p>
<dl class="attribute">
<dt id="pyFTS.probabilistic.kde.KernelSmoothing.h">
<code class="descname">h</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.probabilistic.kde.KernelSmoothing.h" title="Permalink to this definition"></a></dt>
<dd><p>Width parameter</p>
</dd></dl>
<dl class="attribute">
<dt id="pyFTS.probabilistic.kde.KernelSmoothing.kernel">
<code class="descname">kernel</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.probabilistic.kde.KernelSmoothing.kernel" title="Permalink to this definition"></a></dt>
<dd><p>Kernel function</p>
</dd></dl>
<dl class="method">
<dt id="pyFTS.probabilistic.kde.KernelSmoothing.kernel_function">
<code class="descname">kernel_function</code><span class="sig-paren">(</span><em>u</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/kde.html#KernelSmoothing.kernel_function"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.kde.KernelSmoothing.kernel_function" title="Permalink to this definition"></a></dt>
Improving documentation for the Interval and Probabilistic forecasts
2018-09-29 02:35:07 +04:00
<dd><p>Apply the kernel</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>u</strong> – </td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dl class="method">
<dt id="pyFTS.probabilistic.kde.KernelSmoothing.probability">
<code class="descname">probability</code><span class="sig-paren">(</span><em>x</em>, <em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/probabilistic/kde.html#KernelSmoothing.probability"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.probabilistic.kde.KernelSmoothing.probability" title="Permalink to this definition"></a></dt>
<dd><p>Probability of the point x on data</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>x</strong> – </li>
<li><strong>data</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>
</dd></dl>
</div>
</div>
</div>
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Updating the documentation
2018-08-30 23:04:52 +04:00
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