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59 lines
2.0 KiB
C++
59 lines
2.0 KiB
C++
#ifndef ___SUFF_STAT_GAMMA_MIXTURE
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#define ___SUFF_STAT_GAMMA_MIXTURE
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/************************************************************
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The suffStatGammaMixture class is used to obtain the sufficient statistics
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that are neccessary for the EM algorithm to compute the mixture distribution parameters.
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The following notations are used below:
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P(h[i]=k): the probability that position i belongs to the Kth Gamma component.
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teta_t: the current mixture distribution parameters (the alpha, beta, and the probability of each component).
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There are 3 sufficient statistics:
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M_k: the expected number of positions belong to the Kth component.
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sigma(i = 1 to seqLen){P(h[i] = k|data, cur_mixtureDistribution)}
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A_k: sigma(i = 1 to seqLen){P(h[i] = k|data, cur_mixtureDistribution) * E[r|h[i] = k, data, cur_mixtureDistribution]}
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B_k: sigma(i = 1 to seqLen){P(h[i] = k|data, cur_mixtureDistribution) * E[log(r)|h[i] = k, data, cur_mixtureDistribution]}
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************************************************************/
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#include "definitions.h"
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#include "stochasticProcess.h"
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#include "sequenceContainer.h"
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#include "tree.h"
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#include "mixtureDistribution.h"
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#include "computePijComponent.h"
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class suffStatGammaMixture{
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public:
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explicit suffStatGammaMixture(const stochasticProcess& cur_sp, const sequenceContainer& sc, const tree& inTree);
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virtual ~suffStatGammaMixture();
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void computeStatistics();
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void plotStatistics(ofstream & outF);
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MDOUBLE getMk(int comp) const {return _MkVec[comp];}
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MDOUBLE getAk(int comp) const {return _AkVec[comp];}
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MDOUBLE getBk(int comp) const {return _BkVec[comp];}
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MDOUBLE computeQ();
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MDOUBLE computeQ2();
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private:
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MDOUBLE computeStatisticsForComponent(int pos, int componentNum, const computePijGam& cpg);
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void allocatePlaceForSuffStat();
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void computePijForEachComponent(vector<computePijGam>& cpgVec,vector<stochasticProcess>& spVec);
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private:
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Vdouble _MkVec;
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Vdouble _AkVec;
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Vdouble _BkVec;
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const stochasticProcess* _pSp;
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const sequenceContainer* _pSc;
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const tree* _pTree;
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};
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#endif
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