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<div class="section">
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<div class="titlepage"><div><div><h2 class="title" style="clear: both">
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<a name="math_toolkit.ljung_box"></a><a class="link" href="ljung_box.html" title="The Ljung-Box Test">The Ljung-Box Test</a>
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</h2></div></div></div>
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<h4>
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<a name="math_toolkit.ljung_box.h0"></a>
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<span class="phrase"><a name="math_toolkit.ljung_box.synopsis"></a></span><a class="link" href="ljung_box.html#math_toolkit.ljung_box.synopsis">Synopsis</a>
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</h4>
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<pre class="programlisting"><span class="preprocessor">#include</span> <span class="special"><</span><span class="identifier">boost</span><span class="special">/</span><span class="identifier">math</span><span class="special">/</span><span class="identifier">statistics</span><span class="special">/</span><span class="identifier">ljung_box</span><span class="special">.</span><span class="identifier">hpp</span><span class="special">></span>
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<span class="keyword">namespace</span> <span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span><span class="identifier">statistics</span> <span class="special">{</span>
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<span class="keyword">template</span><span class="special"><</span><span class="keyword">class</span> <span class="identifier">RandomAccessIterator</span><span class="special">></span>
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<span class="identifier">std</span><span class="special">::</span><span class="identifier">pair</span><span class="special"><</span><span class="identifier">Real</span><span class="special">,</span> <span class="identifier">Real</span><span class="special">></span> <span class="identifier">ljung_box</span><span class="special">(</span><span class="identifier">RandomAccessIterator</span> <span class="identifier">begin</span><span class="special">,</span> <span class="identifier">RandomAccessIterator</span> <span class="identifier">end</span><span class="special">,</span> <span class="identifier">int64_t</span> <span class="identifier">lags</span> <span class="special">=</span> <span class="special">-</span><span class="number">1</span><span class="special">,</span> <span class="identifier">int64_t</span> <span class="identifier">fit_dof</span> <span class="special">=</span> <span class="number">0</span><span class="special">);</span>
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<span class="keyword">template</span><span class="special"><</span><span class="keyword">class</span> <span class="identifier">RandomAccessContainer</span><span class="special">></span>
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<span class="keyword">auto</span> <span class="identifier">ljung_box</span><span class="special">(</span><span class="identifier">RandomAccessContainer</span> <span class="keyword">const</span> <span class="special">&</span> <span class="identifier">v</span><span class="special">,</span> <span class="identifier">int64_t</span> <span class="identifier">lags</span> <span class="special">=</span> <span class="special">-</span><span class="number">1</span><span class="special">,</span> <span class="identifier">int64_t</span> <span class="identifier">fit_dof</span> <span class="special">=</span> <span class="number">0</span><span class="special">);</span>
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<span class="special">}</span>
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</pre>
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<h4>
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<a name="math_toolkit.ljung_box.h1"></a>
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<span class="phrase"><a name="math_toolkit.ljung_box.background"></a></span><a class="link" href="ljung_box.html#math_toolkit.ljung_box.background">Background</a>
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</h4>
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<p>
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The Ljung-Box test is used to test if residuals from a fitted model have unwanted
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autocorrelation. If autocorrelation exists in the residuals, then presumably
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a model with more parameters can be fitted to the original data and explain
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more of the structure it contains.
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</p>
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<p>
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The test statistic is
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</p>
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<p>
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<span class="inlinemediaobject"><object type="image/svg+xml" data="../../graphs/ljung_box_definition.svg" width="479" height="55"></object></span>
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</p>
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<p>
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where <span class="emphasis"><em>n</em></span> is the length of <span class="emphasis"><em>v</em></span> and ℓ
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is the number of lags.
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</p>
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<p>
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The variance of the statistic slightly exceeds the variance of the chi squared
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distribution, but nonetheless it still is a fairly good test with reasonable
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computational cost.
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</p>
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<p>
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An example use is given below:
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</p>
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<pre class="programlisting"><span class="preprocessor">#include</span> <span class="special"><</span><span class="identifier">vector</span><span class="special">></span>
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<span class="preprocessor">#include</span> <span class="special"><</span><span class="identifier">random</span><span class="special">></span>
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<span class="preprocessor">#include</span> <span class="special"><</span><span class="identifier">iostream</span><span class="special">></span>
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<span class="preprocessor">#include</span> <span class="special"><</span><span class="identifier">boost</span><span class="special">/</span><span class="identifier">math</span><span class="special">/</span><span class="identifier">statistics</span><span class="special">/</span><span class="identifier">ljung_box</span><span class="special">.</span><span class="identifier">hpp</span><span class="special">></span>
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<span class="keyword">using</span> <span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span><span class="identifier">statistics</span><span class="special">::</span><span class="identifier">ljung_box</span><span class="special">;</span>
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<span class="identifier">std</span><span class="special">::</span><span class="identifier">random_device</span> <span class="identifier">rd</span><span class="special">;</span>
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<span class="identifier">std</span><span class="special">::</span><span class="identifier">normal_distribution</span><span class="special"><</span><span class="keyword">double</span><span class="special">></span> <span class="identifier">dis</span><span class="special">(</span><span class="number">0</span><span class="special">,</span> <span class="number">1</span><span class="special">);</span>
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<span class="identifier">std</span><span class="special">::</span><span class="identifier">vector</span><span class="special"><</span><span class="keyword">double</span><span class="special">></span> <span class="identifier">v</span><span class="special">(</span><span class="number">8192</span><span class="special">);</span>
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<span class="keyword">for</span> <span class="special">(</span><span class="keyword">auto</span> <span class="special">&</span> <span class="identifier">x</span> <span class="special">:</span> <span class="identifier">v</span><span class="special">)</span> <span class="special">{</span> <span class="identifier">x</span> <span class="special">=</span> <span class="identifier">dis</span><span class="special">(</span><span class="identifier">rd</span><span class="special">);</span> <span class="special">}</span>
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<span class="keyword">auto</span> <span class="special">[</span><span class="identifier">Q</span><span class="special">,</span> <span class="identifier">p</span><span class="special">]</span> <span class="special">=</span> <span class="identifier">ljung_box</span><span class="special">(</span><span class="identifier">v</span><span class="special">);</span>
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<span class="comment">// Possible output: Q = 5.94734, p = 0.819668</span>
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</pre>
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<p>
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Now if the result is clearly autocorrelated:
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</p>
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<pre class="programlisting"><span class="keyword">for</span> <span class="special">(</span><span class="identifier">size_t</span> <span class="identifier">i</span> <span class="special">=</span> <span class="number">0</span><span class="special">;</span> <span class="identifier">i</span> <span class="special"><</span> <span class="identifier">v</span><span class="special">.</span><span class="identifier">size</span><span class="special">();</span> <span class="special">++</span><span class="identifier">i</span><span class="special">)</span> <span class="special">{</span> <span class="identifier">v</span><span class="special">[</span><span class="identifier">i</span><span class="special">]</span> <span class="special">=</span> <span class="identifier">i</span><span class="special">;</span> <span class="special">}</span>
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<span class="keyword">auto</span> <span class="special">[</span><span class="identifier">Q</span><span class="special">,</span> <span class="identifier">p</span><span class="special">]</span> <span class="special">=</span> <span class="identifier">ljung_box</span><span class="special">(</span><span class="identifier">v</span><span class="special">);</span>
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<span class="comment">// Possible output: Q = 81665.1, p = 0</span>
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</pre>
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<p>
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By default, the number of lags is taken to be the logarithm of the number of
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samples, so that the default complexity is [bigO](<span class="emphasis"><em>n</em></span> ln
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<span class="emphasis"><em>n</em></span>). If you want to calculate a given number of lags, use
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the second argument:
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</p>
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<pre class="programlisting"><span class="identifier">int64_t</span> <span class="identifier">lags</span> <span class="special">=</span> <span class="number">10</span><span class="special">;</span>
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<span class="keyword">auto</span> <span class="special">[</span><span class="identifier">Q</span><span class="special">,</span> <span class="identifier">p</span><span class="special">]</span> <span class="special">=</span> <span class="identifier">ljung_box</span><span class="special">(</span><span class="identifier">v</span><span class="special">,</span><span class="number">10</span><span class="special">);</span>
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</pre>
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<p>
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Finally, it is sometimes relevant to specify how many degrees of freedom were
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used in creating the model from which the residuals were computed. This does
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not affect the test statistic <span class="emphasis"><em>Q</em></span>, but only the <span class="emphasis"><em>p</em></span>-value.
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If you need to specify the number of degrees of freedom, use
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</p>
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<pre class="programlisting"><span class="identifier">int64_t</span> <span class="identifier">fit_dof</span> <span class="special">=</span> <span class="number">2</span><span class="special">;</span>
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<span class="keyword">auto</span> <span class="special">[</span><span class="identifier">Q</span><span class="special">,</span> <span class="identifier">p</span><span class="special">]</span> <span class="special">=</span> <span class="identifier">ljung_box</span><span class="special">(</span><span class="identifier">v</span><span class="special">,</span> <span class="special">-</span><span class="number">1</span><span class="special">,</span> <span class="identifier">fit_dof</span><span class="special">);</span>
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</pre>
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<p>
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For example, if you fit your data with an ARIMA(<span class="emphasis"><em>p</em></span>, <span class="emphasis"><em>q</em></span>)
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model, then <code class="computeroutput"><span class="identifier">fit_dof</span> <span class="special">=</span>
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<span class="identifier">p</span> <span class="special">+</span> <span class="identifier">q</span></code>.
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</p>
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<td align="right"><div class="copyright-footer">Copyright © 2006-2019 Nikhar
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Agrawal, Anton Bikineev, Paul A. Bristow, Marco Guazzone, Christopher Kormanyos,
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Hubert Holin, Bruno Lalande, John Maddock, Jeremy Murphy, Matthew Pulver, Johan
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Råde, Gautam Sewani, Benjamin Sobotta, Nicholas Thompson, Thijs van den Berg,
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Daryle Walker and Xiaogang Zhang<p>
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Distributed under the Boost Software License, Version 1.0. (See accompanying
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file LICENSE_1_0.txt or copy at <a href="http://www.boost.org/LICENSE_1_0.txt" target="_top">http://www.boost.org/LICENSE_1_0.txt</a>)
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