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<div class="titlepage"><div><div><h4 class="title">
<a name="math_toolkit.dist_ref.dists.triangular_dist"></a><a class="link" href="triangular_dist.html" title="Triangular Distribution">Triangular
Distribution</a>
</h4></div></div></div>
<pre class="programlisting"><span class="preprocessor">#include</span> <span class="special">&lt;</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">&gt;</span></pre>
<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>
<span class="keyword">template</span> <span class="special">&lt;</span><span class="keyword">class</span> <span class="identifier">RealType</span> <span class="special">=</span> <span class="keyword">double</span><span class="special">,</span>
<span class="keyword">class</span> <a class="link" href="../../../policy.html" title="Chapter 22. 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&lt;&gt;</a> <span class="special">&gt;</span>
<span class="keyword">class</span> <span class="identifier">triangular_distribution</span><span class="special">;</span>
<span class="keyword">typedef</span> <span class="identifier">triangular_distribution</span><span class="special">&lt;&gt;</span> <span class="identifier">triangular</span><span class="special">;</span>
<span class="keyword">template</span> <span class="special">&lt;</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 22. Policies: Controlling Precision, Error Handling etc">Policy</a><span class="special">&gt;</span>
<span class="keyword">class</span> <span class="identifier">triangular_distribution</span>
<span class="special">{</span>
<span class="keyword">public</span><span class="special">:</span>
<span class="keyword">typedef</span> <span class="identifier">RealType</span> <span class="identifier">value_type</span><span class="special">;</span>
<span class="keyword">typedef</span> <span class="identifier">Policy</span> <span class="identifier">policy_type</span><span class="special">;</span>
<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>
<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>
<span class="comment">// Accessor functions.</span>
<span class="identifier">RealType</span> <span class="identifier">lower</span><span class="special">()</span><span class="keyword">const</span><span class="special">;</span>
<span class="identifier">RealType</span> <span class="identifier">mode</span><span class="special">()</span><span class="keyword">const</span><span class="special">;</span>
<span class="identifier">RealType</span> <span class="identifier">upper</span><span class="special">()</span><span class="keyword">const</span><span class="special">;</span>
<span class="special">};</span> <span class="comment">// class triangular_distribution</span>
<span class="special">}}</span> <span class="comment">// namespaces</span>
</pre>
<p>
The <a href="http://en.wikipedia.org/wiki/Triangular_distribution" target="_top">triangular
distribution</a> is a <a href="http://en.wikipedia.org/wiki/Continuous_distribution" target="_top">continuous</a>
<a href="http://en.wikipedia.org/wiki/Probability_distribution" target="_top">probability
distribution</a> with a lower limit a, <a href="http://en.wikipedia.org/wiki/Mode_%28statistics%29" target="_top">mode
c</a>, and upper limit b.
</p>
<p>
The triangular distribution is often used where the distribution is only
vaguely known, but, like the <a href="http://en.wikipedia.org/wiki/Uniform_distribution_%28continuous%29" target="_top">uniform
distribution</a>, upper and limits are 'known', but a 'best guess',
the mode or center point, is also added. It has been recommended as a
<a href="https://www.jstor.org/stable/2988573" target="_top">proxy for the beta distribution.</a>
The distribution is used in business decision making and project planning.
</p>
<p>
The <a href="http://en.wikipedia.org/wiki/Triangular_distribution" target="_top">triangular
distribution</a> is a distribution with the <a href="http://en.wikipedia.org/wiki/Probability_density_function" target="_top">probability
density function</a>:
</p>
<div class="blockquote"><blockquote class="blockquote"><p>
<span class="serif_italic">f(x) = 2(x-a)/(b-a) (c-a) for a &lt;= x &lt;=
c</span>
</p></blockquote></div>
<div class="blockquote"><blockquote class="blockquote"><p>
<span class="serif_italic">f(x) = 2(b-x)/(b-a) (b-c) for c &lt; x &lt;=
b</span>
</p></blockquote></div>
<p>
Parameter <span class="emphasis"><em>a</em></span> (lower) can be any finite value. Parameter
<span class="emphasis"><em>b</em></span> (upper) can be any finite value &gt; a (lower).
Parameter <span class="emphasis"><em>c</em></span> (mode) a &lt;= c &lt;= b. This is the
most probable value.
</p>
<p>
The <a href="http://en.wikipedia.org/wiki/Random_variate" target="_top">random variate</a>
x must also be finite, and is supported lower &lt;= x &lt;= upper.
</p>
<p>
The triangular distribution may be appropriate when an assumption of a
normal distribution is unjustified because uncertainty is caused by rounding
and quantization from analog to digital conversion. Upper and lower limits
are known, and the most probable value lies midway.
</p>
<p>
The distribution simplifies when the 'best guess' is either the lower or
upper limit - a 90 degree angle triangle. The 001 triangular distribution
which expresses an estimate that the lowest value is the most likely; for
example, you believe that the next-day quoted delivery date is most likely
(knowing that a quicker delivery is impossible - the postman only comes
once a day), and that longer delays are decreasingly likely, and delivery
is assumed to never take more than your upper limit.
</p>
<p>
The following graph illustrates how the <a href="http://en.wikipedia.org/wiki/Probability_density_function" target="_top">probability
density function PDF</a> varies with the various parameters:
</p>
<div class="blockquote"><blockquote class="blockquote"><p>
<span class="inlinemediaobject"><img src="../../../../graphs/triangular_pdf.svg" align="middle"></span>
</p></blockquote></div>
<p>
and cumulative distribution function
</p>
<div class="blockquote"><blockquote class="blockquote"><p>
<span class="inlinemediaobject"><img src="../../../../graphs/triangular_cdf.svg" align="middle"></span>
</p></blockquote></div>
<h5>
<a name="math_toolkit.dist_ref.dists.triangular_dist.h0"></a>
<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
Functions</a>
</h5>
<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>
</pre>
<p>
Constructs a <a href="http://en.wikipedia.org/wiki/triangular_distribution" target="_top">triangular
distribution</a> with lower <span class="emphasis"><em>lower</em></span> (a) and upper
<span class="emphasis"><em>upper</em></span> (b).
</p>
<p>
Requires that the <span class="emphasis"><em>lower</em></span>, <span class="emphasis"><em>mode</em></span>
and <span class="emphasis"><em>upper</em></span> parameters are all finite, otherwise calls
<a class="link" href="../../error_handling.html#math_toolkit.error_handling.domain_error">domain_error</a>.
</p>
<div class="warning"><table border="0" summary="Warning">
<tr>
<td rowspan="2" align="center" valign="top" width="25"><img alt="[Warning]" src="../../../../../../../doc/src/images/warning.png"></td>
<th align="left">Warning</th>
</tr>
<tr><td align="left" valign="top">
<p>
These constructors are slightly different from the analogs provided by
<a href="http://mathworld.wolfram.com" target="_top">Wolfram MathWorld</a>
<a href="http://reference.wolfram.com/language/ref/TriangularDistribution.html" target="_top">Triangular
distribution</a>, where
</p>
<p>
<code class="literal">TriangularDistribution[{min, max}]</code> represents a <span class="bold"><strong>symmetric</strong></span> triangular statistical distribution
giving values between min and max.<br> <code class="literal">TriangularDistribution[]</code>
represents a <span class="bold"><strong>symmetric</strong></span> triangular statistical
distribution giving values between 0 and 1.<br> <code class="literal">TriangularDistribution[{min,
max}, c]</code> represents a triangular distribution with mode at
c (usually <span class="bold"><strong>asymmetric</strong></span>).<br>
</p>
<p>
So, for example, to compute a variance using <a href="http://www.wolframalpha.com/" target="_top">Wolfram
Alpha</a>, use <code class="literal">N[variance[TriangularDistribution{1, +2}],
50]</code>
</p>
</td></tr>
</table></div>
<p>
The parameters of a distribution can be obtained using these member functions:
</p>
<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>
</pre>
<p>
Returns the <span class="emphasis"><em>lower</em></span> parameter of this distribution (default
-1).
</p>
<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>
</pre>
<p>
Returns the <span class="emphasis"><em>mode</em></span> parameter of this distribution (default
0).
</p>
<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>
</pre>
<p>
Returns the <span class="emphasis"><em>upper</em></span> parameter of this distribution (default+1).
</p>
<h5>
<a name="math_toolkit.dist_ref.dists.triangular_dist.h1"></a>
<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
Accessors</a>
</h5>
<p>
All the <a class="link" href="../nmp.html" title="Non-Member Properties">usual non-member accessor
functions</a> that are generic to all distributions are supported:
<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.cdf">Cumulative Distribution Function</a>,
<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.pdf">Probability Density Function</a>,
<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>,
<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>,
<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>,
<a class="link" href="../nmp.html#math_toolkit.dist_ref.nmp.sd">standard deviation</a>,
<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>,
<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>.
</p>
<p>
The domain of the random variable is \lowerto \upper, and the supported
range is lower &lt;= x &lt;= upper.
</p>
<h5>
<a name="math_toolkit.dist_ref.dists.triangular_dist.h2"></a>
<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>
</h5>
<p>
The triangular distribution is implemented with simple arithmetic operators
and so should have errors within an epsilon or two, except quantiles with
arguments nearing the extremes of zero and unity.
</p>
<h5>
<a name="math_toolkit.dist_ref.dists.triangular_dist.h3"></a>
<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>
</h5>
<p>
In the following table, a is the <span class="emphasis"><em>lower</em></span> parameter of
the distribution, c is the <span class="emphasis"><em>mode</em></span> parameter, b is the
<span class="emphasis"><em>upper</em></span> parameter, <span class="emphasis"><em>x</em></span> is the random
variate, <span class="emphasis"><em>p</em></span> is the probability and <span class="emphasis"><em>q = 1-p</em></span>.
</p>
<div class="informaltable"><table class="table">
<colgroup>
<col>
<col>
</colgroup>
<thead><tr>
<th>
<p>
Function
</p>
</th>
<th>
<p>
Implementation Notes
</p>
</th>
</tr></thead>
<tbody>
<tr>
<td>
<p>
pdf
</p>
</td>
<td>
<p>
Using the relation: pdf = 0 for x &lt; mode, 2(x-a)/(b-a)(c-a)
else 2*(b-x)/((b-a)(b-c))
</p>
</td>
</tr>
<tr>
<td>
<p>
cdf
</p>
</td>
<td>
<p>
Using the relation: cdf = 0 for x &lt; mode (x-a)<sup>2</sup>/((b-a)(c-a))
else 1 - (b-x)<sup>2</sup>/((b-a)(b-c))
</p>
</td>
</tr>
<tr>
<td>
<p>
cdf complement
</p>
</td>
<td>
<p>
Using the relation: q = 1 - p
</p>
</td>
</tr>
<tr>
<td>
<p>
quantile
</p>
</td>
<td>
<p>
let p0 = (c-a)/(b-a) the point of inflection on the cdf, then
given probability p and q = 1-p:
</p>
<p>
x = sqrt((b-a)(c-a)p) + a ; for p &lt; p0
</p>
<p>
x = c ; for p == p0
</p>
<p>
x = b - sqrt((b-a)(b-c)q) ; for p &gt; p0
</p>
<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>
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">Wikipedia
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>
<div class="copyright-footer">Copyright © 2006-2021 Nikhar Agrawal, Anton Bikineev, Matthew Borland,
Paul A. Bristow, Marco Guazzone, Christopher Kormanyos, Hubert Holin, Bruno
Lalande, John Maddock, Evan Miller, 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>)
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