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3<title>mixpp: work/mixpp/bdm/stat/libBM.h File Reference</title>
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15<h1>work/mixpp/bdm/stat/libBM.h File Reference</h1>Bayesian Models (bm) that use Bayes rule to learn from observations. <a href="#_details">More...</a>
16<p>
17<code>#include &lt;itpp/itbase.h&gt;</code><br>
18
19<p>
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21Include dependency graph for libBM.h:</div>
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30This graph shows which files directly or indirectly include this file:</div>
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37<p>
38<a href="libBM_8h-source.html">Go to the source code of this file.</a><table border="0" cellpadding="0" cellspacing="0">
39<tr><td></td></tr>
40<tr><td colspan="2"><br><h2>Classes</h2></td></tr>
41<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classRV.html">RV</a></td></tr>
42
43<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Class representing variables, most often random variables.  <a href="classRV.html#_details">More...</a><br></td></tr>
44<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classfnc.html">fnc</a></td></tr>
45
46<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Class representing function of variables.  <a href="classfnc.html#_details">More...</a><br></td></tr>
47<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classBM.html">BM</a></td></tr>
48
49<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.  <a href="classBM.html#_details">More...</a><br></td></tr>
50<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classepdf.html">epdf</a></td></tr>
51
52<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Probability density function with numerical statistics, e.g. posterior density.  <a href="classepdf.html#_details">More...</a><br></td></tr>
53<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmpdf.html">mpdf</a></td></tr>
54
55<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Conditional probability density, e.g. modeling some dependencies.  <a href="classmpdf.html#_details">More...</a><br></td></tr>
56<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classDS.html">DS</a></td></tr>
57
58<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Abstract class for discrete-time sources of data.  <a href="classDS.html#_details">More...</a><br></td></tr>
59</table>
60<hr><a name="_details"></a><h2>Detailed Description</h2>
61Bayesian Models (bm) that use Bayes rule to learn from observations.
62<p>
63<dl class="author" compact><dt><b>Author:</b></dt><dd>Vaclav Smidl.</dd></dl>
64----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty<p>
65Using IT++ for numerical operations ----------------------------------- <hr size="1"><address style="text-align: right;"><small>Generated on Fri Feb 15 18:57:39 2008 for mixpp by&nbsp;
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67<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.3 </small></address>
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