Version 4.1.5

MTDMarkov Class Reference

Mixture Transition Distribution Markov modelling, estimation and simulation. More...

#include <seqpp/MTDMarkov.h>

Inheritance diagram for MTDMarkov:

List of all members.

Public Member Functions
template<class TSeq>
	MTDMarkov (const TSeq &tseq, short mkv_order, short nbseed=NBSEED, int nbiter_max=NBITERMAX, double eps=EPS, bool log=false)
	Constructor 1 from a SequenceSet or a Sequence.
	MTDMarkov (unsigned long **count, short size, short mtd_order, short mkv_order, short nbseed=NBSEED, int nbiter_max=NBITERMAX, double eps=EPS, bool log=false)
	Constructor 2 from a coded-word count.
void	estimate (unsigned long **count, bool decal_required, short mkv_order, short nbseed, int nbiter_max, double eps, bool log)
	performs the estimation [used by each constructor]
	~MTDMarkov ()
	Destructor.
Protected Attributes
mtd_core *	_mtdcore
	Parcimonious Context Trees.

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Detailed Description

Mixture Transition Distribution Markov modelling, estimation and simulation.

MTDMarkov is a Markov object with a different estimation step. This object performs the estimation with the Mixture Transition Distribution algorithm and then transfoms, once per phase, the MTD model in a markovian matrix.

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Constructor & Destructor Documentation

template<class TSeq> MTDMarkov::MTDMarkov (  const TSeq &  tseq, short  mkv_order, short  nbseed = NBSEED, int  nbiter_max = NBITERMAX, double  eps = EPS, bool  log = false )  [inline]

Constructor 1 from a SequenceSet or a Sequence. Parameters: tseq  a set of sequences or a sequence for estimation mkv_order  markovian order on the markovian matrix of the MTD nbseed  number of seeds for the EM algorithm nbiter_max  maximum iterations number of the EM algorithm eps  value of the epsilon of the EM algorithm log  true to log the successive likelihood values

MTDMarkov::MTDMarkov (  unsigned long **  count, short  size, short  mtd_order, short  mkv_order, short  nbseed = NBSEED, int  nbiter_max = NBITERMAX, double  eps = EPS, bool  log = false )  [inline]

Constructor 2 from a coded-word count. Parameters: count  count of all the coded word(base size) of size order+1 for each phase, for estimation size  alphabet size mtd_order  markovian order for the resulting model mkv_order  markovian order on the markovian matrices used in the MTD nbseed  number of seeds for the EM algorithm nbiter_max  maximum iterations number of the EM algorithm eps  value of the epsilon of the EM algorithm log  true to log the successive likelihood values

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The documentation for this class was generated from the following file:

• MTDMarkov.h

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Contributors : M.Baudry, P.Y.Bourguignon, M.Hoebeke, V.Miele, P.Nicolas, G.Nuel, H.Richard, D.Robelin

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