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    <compoundname>arx.h</compoundname>
    <includes local="no">itpp/itbase.h</includes>
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    <includedby refid="bdm_2estim_2arx_8cpp" local="yes">work/git/mixpp/bdm/estim/arx.cpp</includedby>
    <includedby refid="matlab_2mex_2arx_8cpp" local="yes">work/git/mixpp/matlab/mex/arx.cpp</includedby>
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    <includedby refid="arx__test_8cpp" local="no">work/git/mixpp/tests/arx_test.cpp</includedby>
    <incdepgraph>
      <node id="207">
        <label>libBM.h</label>
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        <label>../itpp_ext.h</label>
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        <label>itpp/itbase.h</label>
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        <label>../math/libDC.h</label>
        <link refid="libDC_8h"/>
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      <node id="211">
        <label>work/git/mixpp/bdm/estim/arx.h</label>
        <link refid="arx.h"/>
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        <label>work/git/mixpp/pmsm/sim_var_arx.cpp</label>
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    <innerclass refid="classARX" prot="public">ARX</innerclass>
    <briefdescription>
<para>Bayesian Filtering for generalized autoregressive (<ref refid="classARX" kindref="compound">ARX</ref>) model. </para>    </briefdescription>
    <detaileddescription>
<para><simplesect kind="author"><para>Vaclav Smidl.</para></simplesect>
----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty</para><para>Using IT++ for numerical operations ----------------------------------- </para>    </detaileddescription>
    <programlisting>
<codeline lineno="1"></codeline>
<codeline lineno="13"><highlight class="preprocessor">#ifndef<sp/>AR_H</highlight></codeline>
<codeline lineno="14"><highlight class="preprocessor"></highlight><highlight class="preprocessor">#define<sp/>AR_H</highlight></codeline>
<codeline lineno="15"><highlight class="preprocessor"></highlight><highlight class="normal"></highlight></codeline>
<codeline lineno="16"><highlight class="normal"></highlight><highlight class="preprocessor">#include<sp/>&lt;itpp/itbase.h&gt;</highlight><highlight class="normal"></highlight></codeline>
<codeline lineno="17"><highlight class="normal"></highlight><highlight class="preprocessor">#include<sp/>&quot;../stat/libFN.h&quot;</highlight><highlight class="normal"></highlight></codeline>
<codeline lineno="18"><highlight class="normal"></highlight><highlight class="preprocessor">#include<sp/>&quot;../stat/libEF.h&quot;</highlight><highlight class="normal"></highlight></codeline>
<codeline lineno="19"><highlight class="normal"></highlight></codeline>
<codeline lineno="20"><highlight class="normal"></highlight><highlight class="keyword">using<sp/>namespace<sp/></highlight><highlight class="normal">itpp;</highlight></codeline>
<codeline lineno="21"><highlight class="normal"></highlight></codeline>
<codeline lineno="36" refid="classARX" refkind="compound"><highlight class="keyword">class<sp/></highlight><highlight class="normal"><ref refid="classARX" kindref="compound" tooltip="Linear Autoregressive model with Gaussian noise.">ARX</ref>:<sp/></highlight><highlight class="keyword">public</highlight><highlight class="normal"><sp/><ref refid="classBM" kindref="compound" tooltip="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</ref><sp/>{</highlight></codeline>
<codeline lineno="37"><highlight class="normal"></highlight><highlight class="keyword">protected</highlight><highlight class="normal">:</highlight></codeline>
<codeline lineno="39" refid="classARX_1691d023662beffa1dda611b416c0e27e" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/><ref refid="classegiw" kindref="compound" tooltip="Gauss-inverse-Wishart density stored in LD form.">egiw</ref><sp/><ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>;</highlight></codeline>
<codeline lineno="41" refid="classARX_12291297861dd74ca0175a01f910a0ef7" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/><ref refid="classldmat" kindref="compound" tooltip="Matrix stored in LD form, (typically known as UD).">ldmat</ref><sp/>&amp;<ref refid="classARX_12291297861dd74ca0175a01f910a0ef7" kindref="member" tooltip="cached value of est.V">V</ref>;</highlight></codeline>
<codeline lineno="43" refid="classARX_1a4182c281098b2d86b62518a7493d9be" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/></highlight><highlight class="keywordtype">double</highlight><highlight class="normal"><sp/>&amp;<ref refid="classARX_1a4182c281098b2d86b62518a7493d9be" kindref="member" tooltip="cached value of est.nu">nu</ref>;</highlight></codeline>
<codeline lineno="45" refid="classARX_1e467144efb0a5acbc10dba4eff8638fe" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/></highlight><highlight class="keywordtype">double</highlight><highlight class="normal"><sp/><ref refid="classARX_1e467144efb0a5acbc10dba4eff8638fe" kindref="member" tooltip="forgetting factor">frg</ref>;</highlight></codeline>
<codeline lineno="47" refid="classARX_16d0cd0f0734aa77cdc5e48f1cf6737ec" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/></highlight><highlight class="keywordtype">double</highlight><highlight class="normal"><sp/><ref refid="classARX_16d0cd0f0734aa77cdc5e48f1cf6737ec" kindref="member" tooltip="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</ref>;</highlight></codeline>
<codeline lineno="49" refid="classARX_164ea7c8ff48bf2548bac3e985e24da19" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/></highlight><highlight class="keywordtype">double</highlight><highlight class="normal"><sp/><ref refid="classARX_164ea7c8ff48bf2548bac3e985e24da19" kindref="member" tooltip="total likelihood">tll</ref>;</highlight></codeline>
<codeline lineno="50"><highlight class="normal"></highlight><highlight class="keyword">public</highlight><highlight class="normal">:</highlight></codeline>
<codeline lineno="52" refid="classARX_15fc6c18e73dcc0f1135eef33f42db8be" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/><ref refid="classARX_15fc6c18e73dcc0f1135eef33f42db8be" kindref="member" tooltip="Full constructor.">ARX</ref><sp/>(<ref refid="classRV" kindref="compound" tooltip="Class representing variables, most often random variables.">RV</ref><sp/>&amp;<ref refid="classBM_1af00f0612fabe66241dd507188cdbf88" kindref="member" tooltip="Random variable of the posterior.">rv</ref>,<sp/>mat<sp/>&amp;V0,<sp/></highlight><highlight class="keywordtype">double</highlight><highlight class="normal"><sp/>&amp;nu0,<sp/></highlight><highlight class="keywordtype">double</highlight><highlight class="normal"><sp/>frg0=1.0)<sp/>:<sp/><ref refid="classBM" kindref="compound" tooltip="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</ref>(rv),<ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>(rv,V0,nu0),<sp/><ref refid="classARX_12291297861dd74ca0175a01f910a0ef7" kindref="member" tooltip="cached value of est.V">V</ref>(<ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>._V()),<sp/><ref refid="classARX_1a4182c281098b2d86b62518a7493d9be" kindref="member" tooltip="cached value of est.nu">nu</ref>(<ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>._nu()),<sp/><ref refid="classARX_1e467144efb0a5acbc10dba4eff8638fe" kindref="member" tooltip="forgetting factor">frg</ref>(frg0){<ref refid="classARX_16d0cd0f0734aa77cdc5e48f1cf6737ec" kindref="member" tooltip="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</ref>=<ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>.<ref refid="classegiw_170eb1a0b88459b227f919b425b0d3359" kindref="member" tooltip="logarithm of the normalizing constant, ">lognc</ref>();<ref refid="classARX_164ea7c8ff48bf2548bac3e985e24da19" kindref="member" tooltip="total likelihood">tll</ref>=0.0;};</highlight></codeline>
<codeline lineno="54" refid="classARX_13ccef8dc9dbed00ec74dddc949845d39" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/></highlight><highlight class="keywordtype">void</highlight><highlight class="normal"><sp/><ref refid="classARX_13ccef8dc9dbed00ec74dddc949845d39" kindref="member" tooltip="Set sufficient statistics.">set_parameters</ref>(mat<sp/>&amp;V0,<sp/></highlight><highlight class="keywordtype">double</highlight><highlight class="normal"><sp/>&amp;nu0){<ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>.<ref refid="classegiw_1533e792e1175bfa06d5d595dc5d080d5" kindref="member" tooltip="returns a pointer to the internal statistics. Use with Care!">_V</ref>()=V0;<ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>.<ref refid="classegiw_108029c481ff95d24f093df0573879afe" kindref="member" tooltip="returns a pointer to the internal statistics. Use with Care!">_nu</ref>()=nu0;<ref refid="classARX_16d0cd0f0734aa77cdc5e48f1cf6737ec" kindref="member" tooltip="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</ref>=<ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>.<ref refid="classegiw_170eb1a0b88459b227f919b425b0d3359" kindref="member" tooltip="logarithm of the normalizing constant, ">lognc</ref>();<ref refid="classARX_164ea7c8ff48bf2548bac3e985e24da19" kindref="member" tooltip="total likelihood">tll</ref>=<ref refid="classARX_16d0cd0f0734aa77cdc5e48f1cf6737ec" kindref="member" tooltip="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</ref>;}</highlight></codeline>
<codeline lineno="56" refid="classARX_129f55b43b8b6f5c4a55f6176aa85c494" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/></highlight><highlight class="keywordtype">void</highlight><highlight class="normal"><sp/><ref refid="classARX_129f55b43b8b6f5c4a55f6176aa85c494" kindref="member" tooltip="Returns sufficient statistics.">get_parameters</ref>(mat<sp/>&amp;V0,<sp/></highlight><highlight class="keywordtype">double</highlight><highlight class="normal"><sp/>&amp;nu0){V0=<ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>.<ref refid="classegiw_1533e792e1175bfa06d5d595dc5d080d5" kindref="member" tooltip="returns a pointer to the internal statistics. Use with Care!">_V</ref>().<ref refid="classldmat_15b0515da8dc2293d9e4360b74cc26c9e" kindref="member" tooltip="Conversion to full matrix.">to_mat</ref>();<sp/>nu0=<ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>.<ref refid="classegiw_108029c481ff95d24f093df0573879afe" kindref="member" tooltip="returns a pointer to the internal statistics. Use with Care!">_nu</ref>();}</highlight></codeline>
<codeline lineno="58"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/></highlight><highlight class="keywordtype">void</highlight><highlight class="normal"><sp/><ref refid="classARX_1ba82c956ca893826811aefe1e4af465d" kindref="member" tooltip="Here .">bayes</ref><sp/>(<sp/></highlight><highlight class="keyword">const</highlight><highlight class="normal"><sp/>vec<sp/>&amp;dt<sp/>);</highlight></codeline>
<codeline lineno="59" refid="classARX_19d8eff7a9df81786191a4c55b27e5b8a" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/><ref refid="classepdf" kindref="compound" tooltip="Probability density function with numerical statistics, e.g. posterior density.">epdf</ref>&amp;<sp/><ref refid="classARX_19d8eff7a9df81786191a4c55b27e5b8a" kindref="member" tooltip="Returns a pointer to the epdf representing posterior density on parameters. Use with...">_epdf</ref>()<sp/>{</highlight><highlight class="keywordflow">return</highlight><highlight class="normal"><sp/><ref refid="classARX_1691d023662beffa1dda611b416c0e27e" kindref="member" tooltip="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</ref>;}</highlight></codeline>
<codeline lineno="61"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/>ivec<sp/><ref refid="classARX_1130bb7336aac681ce14b027b8f1409fa" kindref="member" tooltip="Brute force structure estimation.">structure_est</ref>(<ref refid="classegiw" kindref="compound" tooltip="Gauss-inverse-Wishart density stored in LD form.">egiw</ref><sp/>Eg0);</highlight></codeline>
<codeline lineno="63" refid="classARX_1b8827048ceec8999849e2ed15400cae7" refkind="member"><highlight class="normal"><sp/><sp/><sp/><sp/><sp/><sp/><sp/><sp/></highlight><highlight class="keywordtype">double</highlight><highlight class="normal"><sp/><ref refid="classARX_1b8827048ceec8999849e2ed15400cae7" kindref="member" tooltip="access function">_tll</ref>(){</highlight><highlight class="keywordflow">return</highlight><highlight class="normal"><sp/><ref refid="classARX_164ea7c8ff48bf2548bac3e985e24da19" kindref="member" tooltip="total likelihood">tll</ref>;}</highlight></codeline>
<codeline lineno="64"><highlight class="normal">};</highlight></codeline>
<codeline lineno="65"><highlight class="normal"></highlight></codeline>
<codeline lineno="66"><highlight class="normal"></highlight></codeline>
<codeline lineno="67"><highlight class="normal"></highlight><highlight class="preprocessor">#endif<sp/>//<sp/>AR_H</highlight></codeline>
<codeline lineno="68"><highlight class="preprocessor"></highlight><highlight class="normal"></highlight></codeline>
<codeline lineno="69"><highlight class="normal"></highlight></codeline>
    </programlisting>
    <location file="/home/smidl/work/git/mixpp/bdm/estim/arx.h"/>
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