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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.main_faq"></a><a class="link" href="main_faq.html" title="Frequently Asked Questions FAQ">Frequently Asked Questions FAQ</a>
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</h2></div></div></div>
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<div class="orderedlist"><ol class="orderedlist" type="1">
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<li class="listitem">
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<span class="emphasis"><em>I'm a FORTRAN/NAG/SPSS/SAS/Cephes/MathCad/R user and I don't
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see where the functions like dnorm(mean, sd) are in Boost.Math?</em></span>
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<br> Nearly all are provided, and many more like mean, skewness, quantiles,
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complements ... but Boost.Math makes full use of C++, and it looks a bit
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different. But do not panic! See section on construction and the many examples.
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Briefly, the distribution is constructed with the parameters (like location
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and scale) (things after the | in representation like P(X=k|n, p) or ;
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in a common represention of pdf f(x; μσ<sup>2</sup>). Functions like pdf, cdf are called
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with the name of that distribution and the random variate often called
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x or k. For example, <code class="computeroutput"><span class="identifier">normal</span> <span class="identifier">my_norm</span><span class="special">(</span><span class="number">0</span><span class="special">,</span> <span class="number">1</span><span class="special">);</span> <span class="identifier">pdf</span><span class="special">(</span><span class="identifier">my_norm</span><span class="special">,</span> <span class="number">2.0</span><span class="special">);</span></code>
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<br>
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</li>
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<li class="listitem">
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I'm a user of <a href="http://support.sas.com/rnd/app/da/new/probabilityfunctions.html" target="_top">New
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SAS Functions for Computing Probabilities</a>. <br> You will find
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the interface more familar, but to be able to select a distribution (perhaps
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using a string) see the Extras/Future Directions section, and /boost/libs/math/dot_net_example/boost_math.cpp
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for an example that is used to create a C# (C sharp) utility (that you
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might also find useful): see <a href="http://sourceforge.net/projects/distexplorer/" target="_top">Statistical
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Distribution Explorer</a>.<br>
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I'm allegic to reading manuals and prefer to learn from examples.</em></span><br>
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Fear not - you are not alone! Many examples are available for functions
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and distributions. Some are referenced directly from the text. Others can
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be found at \boost_latest_release\libs\math\example. If you are a Visual
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Studio user, you should be able to create projects from each of these,
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making sure that the Boost library is in the include directories list.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>How do I make sure that the Boost library is in the Visual Studio
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include directories list?</em></span><br> You can add an include path,
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for example, your Boost place /boost-latest_release, for example <code class="computeroutput"><span class="identifier">X</span><span class="special">:/</span><span class="identifier">boost_1_45_0</span><span class="special">/</span></code> if you have a separate partition X for
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Boost releases. Or you can use an environment variable BOOST_ROOT set to
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your Boost place, and include that. Visual Studio before 2010 provided
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Tools, Options, VC++ Directories to control directories: Visual Studio
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2010 instead provides property sheets to assist. You may find it convenient
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to create a new one adding \boost-latest_release; to the existing include
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items in $(IncludePath).
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I'm a FORTRAN/NAG/SPSS/SAS/Cephes/MathCad/R user and I don't
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see where the properties like mean, median, mode, variance, skewness of
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distributions are in Boost.Math?</em></span><br> They are all available
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(if defined for the parameters with which you constructed the distribution)
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via <a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.cdf">Cumulative Distribution
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Function</a>, <a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.pdf">Probability
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Density Function</a>, <a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.quantile">Quantile</a>,
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<a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.hazard">Hazard Function</a>,
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<a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.chf">Cumulative Hazard Function</a>,
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<a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.mean">mean</a>, <a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.median">median</a>,
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<a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.mode">mode</a>, <a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.variance">variance</a>,
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<a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.sd">standard deviation</a>,
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<a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.skewness">skewness</a>, <a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.kurtosis">kurtosis</a>, <a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.kurtosis_excess">kurtosis_excess</a>,
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<a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.range">range</a> and <a class="link" href="dist_ref/nmp.html#math_toolkit.dist_ref.nmp.support">support</a>.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I am a C programmer. Can I user Boost.Math with C?</em></span><br>
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Yes you can, including all the special functions, and TR1 functions like
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isnan. They appear as C functions, by being declared as "extern C".
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I am a C# (Basic? F# FORTRAN? Other CLI?) programmer. Can I use
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Boost.Math with C#? (or ...)?</em></span> <br> Yes you can, including
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all the special functions, and TR1 functions like isnan. But you <span class="bold"><strong>must build the Boost.Math as a dynamic library (.dll) and compile
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with the /CLI option</strong></span>. See the boost/math/dot_net_example folder
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which contains an example that builds a simple statistical distribution
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app with a GUI. See <a href="http://sourceforge.net/projects/distexplorer/" target="_top">Statistical
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Distribution Explorer</a> <br>
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</li>
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<li class="listitem">
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<span class="emphasis"><em>What these "policies" things for?</em></span> <br>
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Policies are a powerful (if necessarily complex) fine-grain mechanism that
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allow you to customise the behaviour of the Boost.Math library according
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to your precise needs. See <a class="link" href="../policy.html" title="Chapter 15. Policies: Controlling Precision, Error Handling etc">Policies</a>. But
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if, very probably, the default behaviour suits you, you don't need to know
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more.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I am a C user and expect to see global C-style<code class="computeroutput"><span class="special">::</span><span class="identifier">errno</span></code> set for overflow/errors etc?</em></span>
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<br> You can achieve what you want - see <a class="link" href="pol_ref/error_handling_policies.html" title="Error Handling Policies">error
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handling policies</a> and <a class="link" href="pol_tutorial/user_def_err_pol.html" title="Calling User Defined Error Handlers">user
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error handling</a> and many examples.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I am a C user and expect to silently return a max value for overflow?</em></span>
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<br> You (and C++ users too) can return whatever you want on overflow
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- see <a class="link" href="error_handling.html#math_toolkit.error_handling.overflow_error">overflow_error</a>
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and <a class="link" href="pol_ref/error_handling_policies.html" title="Error Handling Policies">error
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handling policies</a> and several examples.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I don't want any error message for overflow etc?</em></span>
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<br> You can control exactly what happens for all the abnormal conditions,
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including the values returned. See <a class="link" href="error_handling.html#math_toolkit.error_handling.domain_error">domain_error</a>,
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<a class="link" href="error_handling.html#math_toolkit.error_handling.overflow_error">overflow_error</a>
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<a class="link" href="pol_ref/error_handling_policies.html" title="Error Handling Policies">error handling
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policies</a> <a class="link" href="pol_tutorial/user_def_err_pol.html" title="Calling User Defined Error Handlers">user
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error handling</a> etc and examples.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>My environment doesn't allow and/or I don't want exceptions.
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Can I still user Boost.Math?</em></span> <br> Yes but you must customise
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the error handling: see <a class="link" href="pol_tutorial/user_def_err_pol.html" title="Calling User Defined Error Handlers">user
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error handling</a> and <a class="link" href="pol_ref/policy_defaults.html" title="Using Macros to Change the Policy Defaults">changing
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policies defaults</a> .
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</li>
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<li class="listitem">
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<span class="emphasis"><em>The docs are several hundreds of pages long! Can I read the docs
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off-line or on paper?</em></span> <br> Yes - you can download the Boost
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current release of most documentation as a zip of pdfs (including Boost.Math)
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from Sourceforge, for example <a href="https://sourceforge.net/projects/boost/files/boost-docs/1.45.0/boost_pdf_1_45_0.tar.gz/download" target="_top">https://sourceforge.net/projects/boost/files/boost-docs/1.45.0/boost_pdf_1_45_0.tar.gz/download</a>.
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And you can print any pages you need (or even print all pages - but be
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warned that there are several hundred!). Both html and pdf versions are
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highly hyperlinked. The entire Boost.Math pdf can be searched with Adobe
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Reader, Edit, Find ... This can often find what you seek, a partial substitute
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for a full index.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I want a compact version for an embedded application. Can I use
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float precision?</em></span> <br> Yes - by selecting RealType template
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parameter as float: for example normal_distribution<float> your_normal(mean,
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sd); (But double may still be used internally, so space saving may be less
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that you hope for). You can also change the promotion policy, but accuracy
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might be much reduced.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I seem to get somewhat different results compared to other programs.
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Why?</em></span> We hope Boost.Math to be more accurate: our priority is
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accuracy (over speed). See the section on accuracy. But for evaluations
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that require iterations there are parameters which can change the required
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accuracy (see <a class="link" href="../policy.html" title="Chapter 15. Policies: Controlling Precision, Error Handling etc">Policies</a>). You might be able
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to squeeze a little more (or less) accuracy at the cost of runtime.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>Will my program run more slowly compared to other math functions
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and statistical libraries?</em></span> Probably, thought not always, and
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not by too much: our priority is accuracy. For most functions, making sure
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you have the latest compiler version with all optimisations switched on
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is the key to speed. For evaluations that require iteration, you may be
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able to gain a little more speed at the expense of accuracy. See detailed
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suggestions and results on <a class="link" href="../perf.html" title="Chapter 16. Performance">performance</a>.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>How do I handle infinity and NaNs portably?</em></span> <br>
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See <a class="link" href="fp_facets.html" title="Facets for Floating-Point Infinities and NaNs">nonfinite fp_facets</a> for
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Facets for Floating-Point Infinities and NaNs.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>Where are the pre-built libraries?</em></span> <br> Good news
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- you probably don't need any! - just <code class="computeroutput"><span class="preprocessor">#include</span>
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<span class="special"><</span><span class="identifier">boost</span><span class="special">/</span></code><span class="emphasis"><em>math/distribution_you_want></em></span>.
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But in the unlikely event that you do, see <a class="link" href="building.html" title="If and How to Build a Boost.Math Library, and its Examples and Tests">building
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libraries</a>.
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I don't see the function or distribution that I want.</em></span>
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<br> You could try an email to ask the authors - but no promises!
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</li>
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<li class="listitem">
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<span class="emphasis"><em>I need more decimal digits for values/computations.</em></span>
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<br> You can use Boost.Math with <a href="../../../../../libs/multiprecision/doc/html/index.html" target="_top">Boost.Multiprecision</a>:
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typically <a href="../../../../../libs/multiprecision/doc/html/boost_multiprecision/tut/floats/cpp_dec_float.html" target="_top">cpp_dec_float</a>
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is a useful user-defined type to provide a fixed number of decimal digits,
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usually 50 or 100.
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</li>
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<li class="listitem">
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Why can't I write something really simple like <code class="computeroutput"><span class="identifier">cpp_int</span>
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<span class="identifier">one</span><span class="special">(</span><span class="number">1</span><span class="special">);</span> <span class="identifier">cpp_dec_float_50</span>
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<span class="identifier">two</span><span class="special">(</span><span class="number">2</span><span class="special">);</span> <span class="identifier">one</span>
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<span class="special">*</span> <span class="identifier">two</span><span class="special">;</span></code> Because <code class="computeroutput"><span class="identifier">cpp_int</span></code>
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might be bigger than <code class="computeroutput"><span class="identifier">cpp_dec_float</span>
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<span class="identifier">can</span> <span class="identifier">hold</span></code>,
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so you must make an <span class="bold"><strong>explicit</strong></span> conversion.
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See <a href="http://svn.boost.org/svn/boost/trunk/libs/multiprecision/doc/html/boost_multiprecision/intro.html" target="_top">mixed
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multiprecision arithmetic</a> and <a href="http://svn.boost.org/svn/boost/trunk/libs/multiprecision/doc/html/boost_multiprecision/tut/conversions.html" target="_top">conversion</a>.
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</li>
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</ol></div>
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</div>
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<table xmlns:rev="http://www.cs.rpi.edu/~gregod/boost/tools/doc/revision" width="100%"><tr>
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<td align="left"></td>
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<td align="right"><div class="copyright-footer">Copyright © 2006-2010, 2012-2014 Nikhar Agrawal,
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Anton Bikineev, Paul A. Bristow, Marco Guazzone, Christopher Kormanyos, Hubert
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Holin, Bruno Lalande, John Maddock, Jeremy Murphy, Johan Råde, Gautam Sewani,
|
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Benjamin Sobotta, Thijs van den Berg, 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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</p>
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