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<html>
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<title>Distribution Construction Example</title>
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<div class="section math_toolkit_dist_stat_tut_weg_dist_construct_eg">
<div class="titlepage"><div><div><h5 class="title">
<a name="math_toolkit.dist.stat_tut.weg.dist_construct_eg"></a><a class="link" href="dist_construct_eg.html" title="Distribution Construction Example">Distribution
Construction Example</a>
</h5></div></div></div>
<p>
See <a href="../../../../../../../example/distribution_construction.cpp" target="_top">distribution_construction.cpp</a>
for full source code.
</p>
<p>
The structure of distributions is rather different from some other statistical
libraries, for example in less object-oriented language like FORTRAN
and C, that provide a few arguments to each free function. This library
provides each distribution as a template C++ class. A distribution is
constructed with a few arguments, and then member and non-member functions
are used to find values of the distribution, often a function of a random
variate.
</p>
<p>
First we need some includes to access the negative binomial distribution
(and the binomial, beta and gamma too).
</p>
<p>
</p>
<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">negative_binomial</span><span class="special">.</span><span class="identifier">hpp</span><span class="special">></span> <span class="comment">// for negative_binomial_distribution</span>
<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">negative_binomial_distribution</span><span class="special">;</span> <span class="comment">// default type is double.</span>
<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">negative_binomial</span><span class="special">;</span> <span class="comment">// typedef provides default type is double.</span>
<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">binomial</span><span class="special">.</span><span class="identifier">hpp</span><span class="special">></span> <span class="comment">// for binomial_distribution.</span>
<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">beta</span><span class="special">.</span><span class="identifier">hpp</span><span class="special">></span> <span class="comment">// for beta_distribution.</span>
<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">gamma</span><span class="special">.</span><span class="identifier">hpp</span><span class="special">></span> <span class="comment">// for gamma_distribution.</span>
<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">normal</span><span class="special">.</span><span class="identifier">hpp</span><span class="special">></span> <span class="comment">// for normal_distribution.</span>
</pre>
<p>
</p>
<p>
Several examples of constructing distributions follow:
</p>
<p>
First, a negative binomial distribution with 8 successes and a success
fraction 0.25, 25% or 1 in 4, is constructed like this:
</p>
<p>
</p>
<pre class="programlisting"><span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span><span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">double</span><span class="special">></span> <span class="identifier">mydist0</span><span class="special">(</span><span class="number">8.</span><span class="special">,</span> <span class="number">0.25</span><span class="special">);</span>
</pre>
<p>
</p>
<p>
But this is inconveniently long, so we might be tempted to write
</p>
<p>
</p>
<pre class="programlisting"><span class="keyword">using</span> <span class="keyword">namespace</span> <span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">;</span>
</pre>
<p>
</p>
<p>
but this might risk ambiguity with names in std random so *much better
is explicit <code class="computeroutput"><span class="keyword">using</span> <span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span> </code> * ... statements like
</p>
<p>
</p>
<pre class="programlisting"><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">negative_binomial_distribution</span><span class="special">;</span>
</pre>
<p>
</p>
<p>
and we can still reduce typing.
</p>
<p>
Since the vast majority of applications use will be using double precision,
the template argument to the distribution (RealType) defaults to type
double, so we can also write:
</p>
<p>
</p>
<pre class="programlisting"><span class="identifier">negative_binomial_distribution</span><span class="special"><></span> <span class="identifier">mydist9</span><span class="special">(</span><span class="number">8.</span><span class="special">,</span> <span class="number">0.25</span><span class="special">);</span> <span class="comment">// Uses default RealType = double.</span>
</pre>
<p>
</p>
<p>
But the name "negative_binomial_distribution" is still inconveniently
long, so for most distributions, a convenience typedef is provided, for
example:
</p>
<pre class="programlisting"><span class="keyword">typedef</span> <span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">double</span><span class="special">></span> <span class="identifier">negative_binomial</span><span class="special">;</span> <span class="comment">// Reserved name of type double.</span>
</pre>
<div class="caution"><table border="0" summary="Caution">
<tr>
<td rowspan="2" align="center" valign="top" width="25"><img alt="[Caution]" src="../../../../../../../../../doc/src/images/caution.png"></td>
<th align="left">Caution</th>
</tr>
<tr><td align="left" valign="top"><p>
This convenience typedef is <span class="emphasis"><em>not</em></span> provided if a
clash would occur with the name of a function: currently only "beta"
and "gamma" fall into this category.
</p></td></tr>
</table></div>
<p>
So, after a using statement,
</p>
<p>
</p>
<pre class="programlisting"><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">negative_binomial</span><span class="special">;</span>
</pre>
<p>
</p>
<p>
we have a convenient typedef to <code class="computeroutput"><span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">double</span><span class="special">></span></code>:
</p>
<p>
</p>
<pre class="programlisting"><span class="identifier">negative_binomial</span> <span class="identifier">mydist</span><span class="special">(</span><span class="number">8.</span><span class="special">,</span> <span class="number">0.25</span><span class="special">);</span>
</pre>
<p>
</p>
<p>
Some more examples using the convenience typedef:
</p>
<p>
</p>
<pre class="programlisting"><span class="identifier">negative_binomial</span> <span class="identifier">mydist10</span><span class="special">(</span><span class="number">5.</span><span class="special">,</span> <span class="number">0.4</span><span class="special">);</span> <span class="comment">// Both arguments double.</span>
</pre>
<p>
</p>
<p>
And automatic conversion takes place, so you can use integers and floats:
</p>
<p>
</p>
<pre class="programlisting"><span class="identifier">negative_binomial</span> <span class="identifier">mydist11</span><span class="special">(</span><span class="number">5</span><span class="special">,</span> <span class="number">0.4</span><span class="special">);</span> <span class="comment">// Using provided typedef double, int and double arguments.</span>
</pre>
<p>
</p>
<p>
This is probably the most common usage.
</p>
<p>
</p>
<pre class="programlisting"><span class="identifier">negative_binomial</span> <span class="identifier">mydist12</span><span class="special">(</span><span class="number">5.</span><span class="special">,</span> <span class="number">0.4F</span><span class="special">);</span> <span class="comment">// Double and float arguments.</span>
<span class="identifier">negative_binomial</span> <span class="identifier">mydist13</span><span class="special">(</span><span class="number">5</span><span class="special">,</span> <span class="number">1</span><span class="special">);</span> <span class="comment">// Both arguments integer.</span>
</pre>
<p>
</p>
<p>
Similarly for most other distributions like the binomial.
</p>
<p>
</p>
<pre class="programlisting"><span class="identifier">binomial</span> <span class="identifier">mybinomial</span><span class="special">(</span><span class="number">1</span><span class="special">,</span> <span class="number">0.5</span><span class="special">);</span> <span class="comment">// is more concise than</span>
<span class="identifier">binomial_distribution</span><span class="special"><></span> <span class="identifier">mybinomd1</span><span class="special">(</span><span class="number">1</span><span class="special">,</span> <span class="number">0.5</span><span class="special">);</span>
</pre>
<p>
</p>
<p>
For cases when the typdef distribution name would clash with a math special
function (currently only beta and gamma) the typedef is deliberately
not provided, and the longer version of the name must be used. For example
do not use:
</p>
<pre class="programlisting"><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">beta</span><span class="special">;</span>
<span class="identifier">beta</span> <span class="identifier">mybetad0</span><span class="special">(</span><span class="number">1</span><span class="special">,</span> <span class="number">0.5</span><span class="special">);</span> <span class="comment">// Error beta is a math FUNCTION!</span>
</pre>
<p>
Which produces the error messages:
</p>
<pre class="programlisting">error C2146: syntax error : missing ';' before identifier 'mybetad0'
warning C4551: function call missing argument list
error C3861: 'mybetad0': identifier not found
</pre>
<p>
Instead you should use:
</p>
<p>
</p>
<pre class="programlisting"><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">beta_distribution</span><span class="special">;</span>
<span class="identifier">beta_distribution</span><span class="special"><></span> <span class="identifier">mybetad1</span><span class="special">(</span><span class="number">1</span><span class="special">,</span> <span class="number">0.5</span><span class="special">);</span>
</pre>
<p>
</p>
<p>
or for the gamma distribution:
</p>
<p>
</p>
<pre class="programlisting"><span class="identifier">gamma_distribution</span><span class="special"><></span> <span class="identifier">mygammad1</span><span class="special">(</span><span class="number">1</span><span class="special">,</span> <span class="number">0.5</span><span class="special">);</span>
</pre>
<p>
</p>
<p>
We can, of course, still provide the type explicitly thus:
</p>
<p>
</p>
<pre class="programlisting"><span class="comment">// Explicit double precision:</span>
<span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">double</span><span class="special">></span> <span class="identifier">mydist1</span><span class="special">(</span><span class="number">8.</span><span class="special">,</span> <span class="number">0.25</span><span class="special">);</span>
<span class="comment">// Explicit float precision, double arguments are truncated to float:</span>
<span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">float</span><span class="special">></span> <span class="identifier">mydist2</span><span class="special">(</span><span class="number">8.</span><span class="special">,</span> <span class="number">0.25</span><span class="special">);</span>
<span class="comment">// Explicit float precision, integer & double arguments converted to float.</span>
<span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">float</span><span class="special">></span> <span class="identifier">mydist3</span><span class="special">(</span><span class="number">8</span><span class="special">,</span> <span class="number">0.25</span><span class="special">);</span>
<span class="comment">// Explicit float precision, float arguments, so no conversion:</span>
<span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">float</span><span class="special">></span> <span class="identifier">mydist4</span><span class="special">(</span><span class="number">8.F</span><span class="special">,</span> <span class="number">0.25F</span><span class="special">);</span>
<span class="comment">// Explicit float precision, integer arguments promoted to float.</span>
<span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">float</span><span class="special">></span> <span class="identifier">mydist5</span><span class="special">(</span><span class="number">8</span><span class="special">,</span> <span class="number">1</span><span class="special">);</span>
<span class="comment">// Explicit double precision:</span>
<span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">double</span><span class="special">></span> <span class="identifier">mydist6</span><span class="special">(</span><span class="number">8.</span><span class="special">,</span> <span class="number">0.25</span><span class="special">);</span>
<span class="comment">// Explicit long double precision:</span>
<span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="keyword">long</span> <span class="keyword">double</span><span class="special">></span> <span class="identifier">mydist7</span><span class="special">(</span><span class="number">8.</span><span class="special">,</span> <span class="number">0.25</span><span class="special">);</span>
</pre>
<p>
</p>
<p>
And if you have your own RealType called MyFPType, for example NTL RR
(an arbitrary precision type), then we can write:
</p>
<pre class="programlisting"><span class="identifier">negative_binomial_distribution</span><span class="special"><</span><span class="identifier">MyFPType</span><span class="special">></span> <span class="identifier">mydist6</span><span class="special">(</span><span class="number">8</span><span class="special">,</span> <span class="number">1</span><span class="special">);</span> <span class="comment">// Integer arguments -> MyFPType.</span>
</pre>
<h6>
<a name="math_toolkit.dist.stat_tut.weg.dist_construct_eg.h0"></a>
<span><a name="math_toolkit.dist.stat_tut.weg.dist_construct_eg.default_arguments_to_distribution_constructors_"></a></span><a class="link" href="dist_construct_eg.html#math_toolkit.dist.stat_tut.weg.dist_construct_eg.default_arguments_to_distribution_constructors_">Default
arguments to distribution constructors.</a>
</h6>
<p>
Note that default constructor arguments are only provided for some distributions.
So if you wrongly assume a default argument you will get an error message,
for example:
</p>
<pre class="programlisting"><span class="identifier">negative_binomial_distribution</span><span class="special"><></span> <span class="identifier">mydist8</span><span class="special">;</span>
</pre>
<pre class="programlisting">error C2512 no appropriate default constructor available.</pre>
<p>
No default constructors are provided for the negative binomial, because
it is difficult to chose any sensible default values for this distribution.
For other distributions, like the normal distribution, it is obviously
very useful to provide 'standard' defaults for the mean and standard
deviation thus:
</p>
<pre class="programlisting"><span class="identifier">normal_distribution</span><span class="special">(</span><span class="identifier">RealType</span> <span class="identifier">mean</span> <span class="special">=</span> <span class="number">0</span><span class="special">,</span> <span class="identifier">RealType</span> <span class="identifier">sd</span> <span class="special">=</span> <span class="number">1</span><span class="special">);</span>
</pre>
<p>
So in this case we can write:
</p>
<p>
</p>
<pre class="programlisting"> <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">normal</span><span class="special">;</span>
<span class="identifier">normal</span> <span class="identifier">norm1</span><span class="special">;</span> <span class="comment">// Standard normal distribution.</span>
<span class="identifier">normal</span> <span class="identifier">norm2</span><span class="special">(</span><span class="number">2</span><span class="special">);</span> <span class="comment">// Mean = 2, std deviation = 1.</span>
<span class="identifier">normal</span> <span class="identifier">norm3</span><span class="special">(</span><span class="number">2</span><span class="special">,</span> <span class="number">3</span><span class="special">);</span> <span class="comment">// Mean = 2, std deviation = 3.</span>
<span class="keyword">return</span> <span class="number">0</span><span class="special">;</span>
<span class="special">}</span> <span class="comment">// int main()</span>
</pre>
<p>
</p>
<p>
There is no useful output from this program, of course.
</p>
</div>
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Lalande, Johan Råde, Gautam Sewani, Thijs van den Berg and Benjamin Sobotta<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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