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<title>Triangular Distribution</title>
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<div class="section">
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<div class="titlepage"><div><div><h4 class="title">
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<a name="math_toolkit.dist_ref.dists.triangular_dist"></a><a class="link" href="triangular_dist.html" title="Triangular Distribution">Triangular
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Distribution</a>
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</h4></div></div></div>
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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">distributions</span><span class="special">/</span><span class="identifier">triangular</span><span class="special">.</span><span class="identifier">hpp</span><span class="special">></span></pre>
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<pre class="programlisting"><span class="keyword">namespace</span> <span class="identifier">boost</span><span class="special">{</span> <span class="keyword">namespace</span> <span class="identifier">math</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">RealType</span> <span class="special">=</span> <span class="keyword">double</span><span class="special">,</span>
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<span class="keyword">class</span> <a class="link" href="../../../policy.html" title="Chapter 19. Policies: Controlling Precision, Error Handling etc">Policy</a> <span class="special">=</span> <a class="link" href="../../pol_ref/pol_ref_ref.html" title="Policy Class Reference">policies::policy<></a> <span class="special">></span>
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<span class="keyword">class</span> <span class="identifier">triangular_distribution</span><span class="special">;</span>
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<span class="keyword">typedef</span> <span class="identifier">triangular_distribution</span><span class="special"><></span> <span class="identifier">triangular</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">RealType</span><span class="special">,</span> <span class="keyword">class</span> <a class="link" href="../../../policy.html" title="Chapter 19. Policies: Controlling Precision, Error Handling etc">Policy</a><span class="special">></span>
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<span class="keyword">class</span> <span class="identifier">triangular_distribution</span>
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<span class="special">{</span>
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<span class="keyword">public</span><span class="special">:</span>
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<span class="keyword">typedef</span> <span class="identifier">RealType</span> <span class="identifier">value_type</span><span class="special">;</span>
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<span class="keyword">typedef</span> <span class="identifier">Policy</span> <span class="identifier">policy_type</span><span class="special">;</span>
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<span class="identifier">triangular_distribution</span><span class="special">(</span><span class="identifier">RealType</span> <span class="identifier">lower</span> <span class="special">=</span> <span class="special">-</span><span class="number">1</span><span class="special">,</span> <span class="identifier">RealType</span> <span class="identifier">mode</span> <span class="special">=</span> <span class="number">0</span><span class="special">)</span> <span class="identifier">RealType</span> <span class="identifier">upper</span> <span class="special">=</span> <span class="number">1</span><span class="special">);</span> <span class="comment">// Constructor.</span>
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<span class="special">:</span> <span class="identifier">m_lower</span><span class="special">(</span><span class="identifier">lower</span><span class="special">),</span> <span class="identifier">m_mode</span><span class="special">(</span><span class="identifier">mode</span><span class="special">),</span> <span class="identifier">m_upper</span><span class="special">(</span><span class="identifier">upper</span><span class="special">)</span> <span class="comment">// Default is -1, 0, +1 symmetric triangular distribution.</span>
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<span class="comment">// Accessor functions.</span>
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<span class="identifier">RealType</span> <span class="identifier">lower</span><span class="special">()</span><span class="keyword">const</span><span class="special">;</span>
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<span class="identifier">RealType</span> <span class="identifier">mode</span><span class="special">()</span><span class="keyword">const</span><span class="special">;</span>
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<span class="identifier">RealType</span> <span class="identifier">upper</span><span class="special">()</span><span class="keyword">const</span><span class="special">;</span>
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<span class="special">};</span> <span class="comment">// class triangular_distribution</span>
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<span class="special">}}</span> <span class="comment">// namespaces</span>
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</pre>
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<p>
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The <a href="http://en.wikipedia.org/wiki/Triangular_distribution" target="_top">triangular
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distribution</a> is a <a href="http://en.wikipedia.org/wiki/Continuous_distribution" target="_top">continuous</a>
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<a href="http://en.wikipedia.org/wiki/Probability_distribution" target="_top">probability
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distribution</a> with a lower limit a, <a href="http://en.wikipedia.org/wiki/Mode_%28statistics%29" target="_top">mode
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c</a>, and upper limit b.
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</p>
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<p>
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The triangular distribution is often used where the distribution is only
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vaguely known, but, like the <a href="http://en.wikipedia.org/wiki/Uniform_distribution_%28continuous%29" target="_top">uniform
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distribution</a>, upper and limits are 'known', but a 'best guess',
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the mode or center point, is also added. It has been recommended as a
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<a href="http://www.worldscibooks.com/mathematics/etextbook/5720/5720_chap1.pdf" target="_top">proxy
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for the beta distribution.</a> The distribution is used in business
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decision making and project planning.
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</p>
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<p>
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The <a href="http://en.wikipedia.org/wiki/Triangular_distribution" target="_top">triangular
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distribution</a> is a distribution with the <a href="http://en.wikipedia.org/wiki/Probability_density_function" target="_top">probability
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density function</a>:
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</p>
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<div class="blockquote"><blockquote class="blockquote"><p>
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<span class="serif_italic">f(x) =</span>
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</p></blockquote></div>
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<div class="blockquote"><blockquote class="blockquote"><p>
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<span class="serif_italic">
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<div class="blockquote"><blockquote class="blockquote">
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<p>
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2(x-a)/(b-a) (c-a)
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</p>
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<div class="blockquote"><blockquote class="blockquote"><p>
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for a <= x <= c
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</p></blockquote></div>
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</blockquote></div>
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</span>
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</p></blockquote></div>
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<div class="blockquote"><blockquote class="blockquote"><p>
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<span class="serif_italic">
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<div class="blockquote"><blockquote class="blockquote">
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<p>
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2(b-x)/(b-a) (b-c)
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</p>
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<div class="blockquote"><blockquote class="blockquote"><p>
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for c < x <= b
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</p></blockquote></div>
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</blockquote></div>
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</span>
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</p></blockquote></div>
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<p>
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Parameter <span class="emphasis"><em>a</em></span> (lower) can be any finite value. Parameter
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<span class="emphasis"><em>b</em></span> (upper) can be any finite value > a (lower).
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Parameter <span class="emphasis"><em>c</em></span> (mode) a <= c <= b. This is the
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most probable value.
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</p>
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<p>
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The <a href="http://en.wikipedia.org/wiki/Random_variate" target="_top">random variate</a>
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x must also be finite, and is supported lower <= x <= upper.
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</p>
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<p>
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The triangular distribution may be appropriate when an assumption of a
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normal distribution is unjustified because uncertainty is caused by rounding
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and quantization from analog to digital conversion. Upper and lower limits
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are known, and the most probable value lies midway.
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</p>
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<p>
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The distribution simplifies when the 'best guess' is either the lower or
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upper limit - a 90 degree angle triangle. The 001 triangular distribution
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which expresses an estimate that the lowest value is the most likely; for
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example, you believe that the next-day quoted delivery date is most likely
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(knowing that a quicker delivery is impossible - the postman only comes
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once a day), and that longer delays are decreasingly likely, and delivery
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is assumed to never take more than your upper limit.
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</p>
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<p>
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The following graph illustrates how the <a href="http://en.wikipedia.org/wiki/Probability_density_function" target="_top">probability
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density function PDF</a> varies with the various parameters:
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</p>
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<div class="blockquote"><blockquote class="blockquote"><p>
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<span class="inlinemediaobject"><img src="../../../../graphs/triangular_pdf.svg" align="middle"></span>
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</p></blockquote></div>
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<p>
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and cumulative distribution function
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</p>
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<div class="blockquote"><blockquote class="blockquote"><p>
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<span class="inlinemediaobject"><img src="../../../../graphs/triangular_cdf.svg" align="middle"></span>
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</p></blockquote></div>
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<h5>
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<a name="math_toolkit.dist_ref.dists.triangular_dist.h0"></a>
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<span class="phrase"><a name="math_toolkit.dist_ref.dists.triangular_dist.member_functions"></a></span><a class="link" href="triangular_dist.html#math_toolkit.dist_ref.dists.triangular_dist.member_functions">Member
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Functions</a>
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</h5>
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<pre class="programlisting"><span class="identifier">triangular_distribution</span><span class="special">(</span><span class="identifier">RealType</span> <span class="identifier">lower</span> <span class="special">=</span> <span class="number">0</span><span class="special">,</span> <span class="identifier">RealType</span> <span class="identifier">mode</span> <span class="special">=</span> <span class="number">0</span> <span class="identifier">RealType</span> <span class="identifier">upper</span> <span class="special">=</span> <span class="number">1</span><span class="special">);</span>
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</pre>
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<p>
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Constructs a <a href="http://en.wikipedia.org/wiki/triangular_distribution" target="_top">triangular
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distribution</a> with lower <span class="emphasis"><em>lower</em></span> (a) and upper
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<span class="emphasis"><em>upper</em></span> (b).
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</p>
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<p>
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Requires that the <span class="emphasis"><em>lower</em></span>, <span class="emphasis"><em>mode</em></span>
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and <span class="emphasis"><em>upper</em></span> parameters are all finite, otherwise calls
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<a class="link" href="../../error_handling.html#math_toolkit.error_handling.domain_error">domain_error</a>.
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</p>
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<div class="warning"><table border="0" summary="Warning">
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<tr>
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<td rowspan="2" align="center" valign="top" width="25"><img alt="[Warning]" src="../../../../../../../doc/src/images/warning.png"></td>
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<th align="left">Warning</th>
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</tr>
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<tr><td align="left" valign="top">
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<p>
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These constructors are slightly different from the analogs provided by
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<a href="http://mathworld.wolfram.com" target="_top">Wolfram MathWorld</a>
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<a href="http://reference.wolfram.com/language/ref/TriangularDistribution.html" target="_top">Triangular
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distribution</a>, where
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</p>
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<p>
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<code class="literal">TriangularDistribution[{min, max}]</code> represents a <span class="bold"><strong>symmetric</strong></span> triangular statistical distribution
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giving values between min and max.<br> <code class="literal">TriangularDistribution[]</code>
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represents a <span class="bold"><strong>symmetric</strong></span> triangular statistical
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distribution giving values between 0 and 1.<br> <code class="literal">TriangularDistribution[{min,
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max}, c]</code> represents a triangular distribution with mode at
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c (usually <span class="bold"><strong>asymmetric</strong></span>).<br>
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</p>
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<p>
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So, for example, to compute a variance using <a href="http://www.wolframalpha.com/" target="_top">Wolfram
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Alpha</a>, use <code class="literal">N[variance[TriangularDistribution{1, +2}],
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50]</code>
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</p>
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</td></tr>
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</table></div>
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<p>
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The parameters of a distribution can be obtained using these member functions:
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</p>
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<pre class="programlisting"><span class="identifier">RealType</span> <span class="identifier">lower</span><span class="special">()</span><span class="keyword">const</span><span class="special">;</span>
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</pre>
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<p>
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Returns the <span class="emphasis"><em>lower</em></span> parameter of this distribution (default
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-1).
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</p>
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<pre class="programlisting"><span class="identifier">RealType</span> <span class="identifier">mode</span><span class="special">()</span><span class="keyword">const</span><span class="special">;</span>
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</pre>
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<p>
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Returns the <span class="emphasis"><em>mode</em></span> parameter of this distribution (default
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0).
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</p>
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<pre class="programlisting"><span class="identifier">RealType</span> <span class="identifier">upper</span><span class="special">()</span><span class="keyword">const</span><span class="special">;</span>
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</pre>
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<p>
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Returns the <span class="emphasis"><em>upper</em></span> parameter of this distribution (default+1).
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</p>
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<h5>
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<a name="math_toolkit.dist_ref.dists.triangular_dist.h1"></a>
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<span class="phrase"><a name="math_toolkit.dist_ref.dists.triangular_dist.non_member_accessors"></a></span><a class="link" href="triangular_dist.html#math_toolkit.dist_ref.dists.triangular_dist.non_member_accessors">Non-member
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Accessors</a>
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</h5>
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<p>
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All the <a class="link" href="../nmp.html" title="Non-Member Properties">usual non-member accessor
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functions</a> that are generic to all distributions are supported:
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<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.cdf">Cumulative Distribution Function</a>,
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<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.pdf">Probability Density Function</a>,
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<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.quantile">Quantile</a>, <a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.hazard">Hazard Function</a>, <a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.chf">Cumulative Hazard Function</a>,
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<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.mean">mean</a>, <a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.median">median</a>,
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<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.mode">mode</a>, <a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.variance">variance</a>,
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<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.sd">standard deviation</a>,
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<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.skewness">skewness</a>, <a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.kurtosis">kurtosis</a>, <a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.kurtosis_excess">kurtosis_excess</a>,
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<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.range">range</a> and <a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.support">support</a>.
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</p>
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<p>
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The domain of the random variable is \lowerto \upper, and the supported
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range is lower <= x <= upper.
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</p>
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<h5>
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<a name="math_toolkit.dist_ref.dists.triangular_dist.h2"></a>
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<span class="phrase"><a name="math_toolkit.dist_ref.dists.triangular_dist.accuracy"></a></span><a class="link" href="triangular_dist.html#math_toolkit.dist_ref.dists.triangular_dist.accuracy">Accuracy</a>
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</h5>
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<p>
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The triangular distribution is implemented with simple arithmetic operators
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and so should have errors within an epsilon or two, except quantiles with
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arguments nearing the extremes of zero and unity.
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</p>
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<h5>
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<a name="math_toolkit.dist_ref.dists.triangular_dist.h3"></a>
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<span class="phrase"><a name="math_toolkit.dist_ref.dists.triangular_dist.implementation"></a></span><a class="link" href="triangular_dist.html#math_toolkit.dist_ref.dists.triangular_dist.implementation">Implementation</a>
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</h5>
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<p>
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In the following table, a is the <span class="emphasis"><em>lower</em></span> parameter of
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the distribution, c is the <span class="emphasis"><em>mode</em></span> parameter, b is the
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<span class="emphasis"><em>upper</em></span> parameter, <span class="emphasis"><em>x</em></span> is the random
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variate, <span class="emphasis"><em>p</em></span> is the probability and <span class="emphasis"><em>q = 1-p</em></span>.
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</p>
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<div class="informaltable"><table class="table">
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<colgroup>
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<col>
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<col>
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</colgroup>
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<thead><tr>
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<th>
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<p>
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Function
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</p>
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</th>
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<th>
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<p>
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Implementation Notes
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</p>
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</th>
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</tr></thead>
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<tbody>
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<tr>
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<td>
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<p>
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pdf
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</p>
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</td>
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<td>
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<p>
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Using the relation: pdf = 0 for x < mode, 2(x-a)/(b-a)(c-a)
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else 2*(b-x)/((b-a)(b-c))
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</p>
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</td>
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</tr>
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<tr>
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<td>
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<p>
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cdf
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</p>
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</td>
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<td>
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<p>
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Using the relation: cdf = 0 for x < mode (x-a)<sup>2</sup>/((b-a)(c-a))
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else 1 - (b-x)<sup>2</sup>/((b-a)(b-c))
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</p>
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</td>
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</tr>
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<tr>
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<td>
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<p>
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cdf complement
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</p>
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</td>
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<td>
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<p>
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Using the relation: q = 1 - p
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</p>
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</td>
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</tr>
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<tr>
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<td>
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<p>
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quantile
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</p>
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</td>
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<td>
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<p>
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let p0 = (c-a)/(b-a) the point of inflection on the cdf, then
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given probability p and q = 1-p:
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</p>
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<p>
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x = sqrt((b-a)(c-a)p) + a ; for p < p0
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</p>
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<p>
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x = c ; for p == p0
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</p>
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<p>
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x = b - sqrt((b-a)(b-c)q) ; for p > p0
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</p>
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<p>
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(See <a href="../../../../../../../boost/math/distributions/triangular.hpp" target="_top">/boost/math/distributions/triangular.hpp</a>
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for details.)
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</p>
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</td>
|
|
</tr>
|
|
<tr>
|
|
<td>
|
|
<p>
|
|
quantile from the complement
|
|
</p>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
As quantile (See <a href="../../../../../../../boost/math/distributions/triangular.hpp" target="_top">/boost/math/distributions/triangular.hpp</a>
|
|
for details.)
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td>
|
|
<p>
|
|
mean
|
|
</p>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
(a + b + 3) / 3
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td>
|
|
<p>
|
|
variance
|
|
</p>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
(a<sup>2</sup>+b<sup>2</sup>+c<sup>2</sup> - ab - ac - bc)/18
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td>
|
|
<p>
|
|
mode
|
|
</p>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
c
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td>
|
|
<p>
|
|
skewness
|
|
</p>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
(See <a href="../../../../../../../boost/math/distributions/triangular.hpp" target="_top">/boost/math/distributions/triangular.hpp</a>
|
|
for details).
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td>
|
|
<p>
|
|
kurtosis
|
|
</p>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
12/5
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td>
|
|
<p>
|
|
kurtosis excess
|
|
</p>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
-3/5
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table></div>
|
|
<p>
|
|
Some 'known good' test values were obtained using <a href="http://www.wolframalpha.com/" target="_top">Wolfram
|
|
Alpha</a>.
|
|
</p>
|
|
<h5>
|
|
<a name="math_toolkit.dist_ref.dists.triangular_dist.h4"></a>
|
|
<span class="phrase"><a name="math_toolkit.dist_ref.dists.triangular_dist.references"></a></span><a class="link" href="triangular_dist.html#math_toolkit.dist_ref.dists.triangular_dist.references">References</a>
|
|
</h5>
|
|
<div class="itemizedlist"><ul class="itemizedlist" style="list-style-type: disc; ">
|
|
<li class="listitem">
|
|
<a href="http://en.wikipedia.org/wiki/Triangular_distribution" target="_top">Wikpedia
|
|
triangular distribution</a>
|
|
</li>
|
|
<li class="listitem">
|
|
<a href="http://mathworld.wolfram.com/TriangularDistribution.html" target="_top">Weisstein,
|
|
Eric W. "Triangular Distribution." From MathWorld--A Wolfram
|
|
Web Resource.</a>
|
|
</li>
|
|
<li class="listitem">
|
|
Evans, M.; Hastings, N.; and Peacock, B. "Triangular Distribution."
|
|
Ch. 40 in Statistical Distributions, 3rd ed. New York: Wiley, pp. 187-188,
|
|
2000, ISBN - 0471371246.
|
|
</li>
|
|
<li class="listitem">
|
|
<a href="http://www.measurement.sk/2002/S1/Wimmer2.pdf" target="_top">Gejza Wimmer,
|
|
Viktor Witkovsky and Tomas Duby, Measurement Science Review, Volume
|
|
2, Section 1, 2002, Proper Rounding Of The Measurement Results Under
|
|
The Assumption Of Triangular Distribution.</a>
|
|
</li>
|
|
</ul></div>
|
|
</div>
|
|
<table xmlns:rev="http://www.cs.rpi.edu/~gregod/boost/tools/doc/revision" width="100%"><tr>
|
|
<td align="left"></td>
|
|
<td align="right"><div class="copyright-footer">Copyright © 2006-2019 Nikhar
|
|
Agrawal, Anton Bikineev, Paul A. Bristow, Marco Guazzone, Christopher Kormanyos,
|
|
Hubert Holin, Bruno Lalande, John Maddock, Jeremy Murphy, Matthew Pulver, Johan
|
|
Råde, Gautam Sewani, Benjamin Sobotta, Nicholas Thompson, Thijs van den Berg,
|
|
Daryle Walker and Xiaogang Zhang<p>
|
|
Distributed under the Boost Software License, Version 1.0. (See accompanying
|
|
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>)
|
|
</p>
|
|
</div></td>
|
|
</tr></table>
|
|
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