Changeset 323 for doc/html/classbdm_1_1MixEF.html
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- 04/23/09 21:12:23 (16 years ago)
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doc/html/classbdm_1_1MixEF.html
r312 r323 115 115 <a class="el" href="classbdm_1_1emix.html">emix</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1MixEF.html#edc50e9640f049b846084748b18469a2">epredictor</a> () const </td></tr> 116 116 117 <tr><td class="mdescLeft"> </td><td class="mdescRight">Constructs a predictive density <img class="formulaInl" alt="$ f(d_{t+1} |d_{t}, \ldots d_{0}) $" src="form_ 49.png">. <br></td></tr>117 <tr><td class="mdescLeft"> </td><td class="mdescRight">Constructs a predictive density <img class="formulaInl" alt="$ f(d_{t+1} |d_{t}, \ldots d_{0}) $" src="form_53.png">. <br></td></tr> 118 118 <tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="f0dfb4375fef4e61c4cb062e5bac7c8c"></a><!-- doxytag: member="bdm::MixEF::flatten" ref="f0dfb4375fef4e61c4cb062e5bac7c8c" args="(const BMEF *M2)" --> 119 119 void </td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1MixEF.html#f0dfb4375fef4e61c4cb062e5bac7c8c">flatten</a> (const <a class="el" href="classbdm_1_1BMEF.html">BMEF</a> *M2)</td></tr> … … 182 182 Array< <a class="el" href="classbdm_1_1BMEF.html">BMEF</a> * > </td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1MixEF.html#90c21ab5a2af56d4b49e2eaef6eccc08">Coms</a></td></tr> 183 183 184 <tr><td class="mdescLeft"> </td><td class="mdescRight">Models for Components of <img class="formulaInl" alt="$\theta_i$" src="form_1 5.png">. <br></td></tr>184 <tr><td class="mdescLeft"> </td><td class="mdescRight">Models for Components of <img class="formulaInl" alt="$\theta_i$" src="form_17.png">. <br></td></tr> 185 185 <tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="e39faa70cebadc3296bd249040105e86"></a><!-- doxytag: member="bdm::MixEF::weights" ref="e39faa70cebadc3296bd249040105e86" args="" --> 186 186 <a class="el" href="classbdm_1_1multiBM.html">multiBM</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1MixEF.html#e39faa70cebadc3296bd249040105e86">weights</a></td></tr> … … 234 234 235 235 <tr><td class="mdescLeft"> </td><td class="mdescRight">Set boolean options from a string. <br></td></tr> 236 <tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name=" aa5d1f7e638db229403e3917bf155ee3"></a><!-- doxytag: member="bdm::MixEF::log_add" ref="aa5d1f7e638db229403e3917bf155ee3" args="(logger *L, const string &name="")" -->237 v oid </td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1BM.html#aa5d1f7e638db229403e3917bf155ee3">log_add</a> (<a class="el" href="classbdm_1_1logger.html">logger</a> *L, const string &name="")</td></tr>236 <tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="2298ca6af9b13a78a4c9e18ab43f1827"></a><!-- doxytag: member="bdm::MixEF::log_add" ref="2298ca6af9b13a78a4c9e18ab43f1827" args="(logger &L, const string &name="")" --> 237 virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1BM.html#2298ca6af9b13a78a4c9e18ab43f1827">log_add</a> (<a class="el" href="classbdm_1_1logger.html">logger</a> &L, const string &name="")</td></tr> 238 238 239 239 <tr><td class="mdescLeft"> </td><td class="mdescRight">Add all logged variables to a <a class="el" href="classbdm_1_1logger.html" title="Class for storing results (and semi-results) of an experiment.">logger</a>. <br></td></tr> 240 <tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name=" 0647606eefbf294623bf664971c7d461"></a><!-- doxytag: member="bdm::MixEF::logit" ref="0647606eefbf294623bf664971c7d461" args="(logger *L)" -->241 v oid </td><td class="memItemRight" valign="bottom"><b>logit</b> (<a class="el" href="classbdm_1_1logger.html">logger</a> *L)</td></tr>240 <tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="b517e1679eaa94e803ea4cd0b8efbcd7"></a><!-- doxytag: member="bdm::MixEF::logit" ref="b517e1679eaa94e803ea4cd0b8efbcd7" args="(logger &L)" --> 241 virtual void </td><td class="memItemRight" valign="bottom"><b>logit</b> (<a class="el" href="classbdm_1_1logger.html">logger</a> &L)</td></tr> 242 242 243 243 <tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="109c1a626a69031658e3a44e9e500cca"></a><!-- doxytag: member="bdm::MixEF::LIDs" ref="109c1a626a69031658e3a44e9e500cca" args="" --> … … 254 254 <p> 255 255 An approximate estimation method for models with latent discrete variable, such as mixture models of the following kind: <p class="formulaDsp"> 256 <img class="formulaDsp" alt="\[ f(y_t|\psi_t, \Theta) = \sum_{i=1}^{n} w_i f(y_t|\psi_t, \theta_i) \]" src="form_1 2.png">257 <p> 258 where <img class="formulaInl" alt="$\psi$" src="form_1 3.png"> is a known function of past outputs, <img class="formulaInl" alt="$w=[w_1,\ldots,w_n]$" src="form_14.png"> are component weights, and component parameters <img class="formulaInl" alt="$\theta_i$" src="form_15.png"> are assumed to be mutually independent. <img class="formulaInl" alt="$\Theta$" src="form_16.png"> is an aggregation af all component parameters and weights, i.e. <img class="formulaInl" alt="$\Theta = [\theta_1,\ldots,\theta_n,w]$" src="form_17.png">.<p>256 <img class="formulaDsp" alt="\[ f(y_t|\psi_t, \Theta) = \sum_{i=1}^{n} w_i f(y_t|\psi_t, \theta_i) \]" src="form_14.png"> 257 <p> 258 where <img class="formulaInl" alt="$\psi$" src="form_15.png"> is a known function of past outputs, <img class="formulaInl" alt="$w=[w_1,\ldots,w_n]$" src="form_16.png"> are component weights, and component parameters <img class="formulaInl" alt="$\theta_i$" src="form_17.png"> are assumed to be mutually independent. <img class="formulaInl" alt="$\Theta$" src="form_18.png"> is an aggregation af all component parameters and weights, i.e. <img class="formulaInl" alt="$\Theta = [\theta_1,\ldots,\theta_n,w]$" src="form_19.png">.<p> 259 259 The characteristic feature of this model is that if the exact values of the latent variable were known, estimation of the parameters can be handled by a single model. For example, for the case of mixture models, posterior density for each component parameters would be a BayesianModel from Exponential Family.<p> 260 260 This class uses EM-style type algorithms for estimation of its parameters. Under this simplification, the posterior density is a product of exponential family members, hence under EM-style approximate estimation this class itself belongs to the exponential family.<p> … … 335 335 <li><a class="el" href="mixef_8h-source.html">mixef.h</a><li>mixef.cpp</ul> 336 336 </div> 337 <hr size="1"><address style="text-align: right;"><small>Generated on Thu Apr 9 14:33:212009 for mixpp by 337 <hr size="1"><address style="text-align: right;"><small>Generated on Thu Apr 23 21:06:45 2009 for mixpp by 338 338 <a href="http://www.doxygen.org/index.html"> 339 339 <img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address>