non-0-mean prior methods

Collaboration diagram for non-0-mean prior methods:

Functions
virtual void	MVnorm::update (const Grp &, const SigmaI &, const Grp &, const SigmaI &, const gsl_rng *)=0
	Gaussian likelihood, Gaussian prior. More...
virtual void	MVnorm::update (const Grp &, const SigmaI &, const Grp &, const double &, const SigmaI &, const gsl_rng *)=0
	Gaussian likelihood, Student- \(t\) prior. More...
virtual void	MVnorm::update (const Grp &, const Qgrp &, const SigmaI &, const Grp &, const SigmaI &, const gsl_rng *)=0
	Student- \(t\) likelihood, Gaussian prior. More...
virtual void	MVnorm::update (const Grp &, const Qgrp &, const SigmaI &, const Grp &, const double &, const SigmaI &, const gsl_rng *)=0
	Student- \(t\) likelihood, Student- \(t\) prior. More...
virtual void	Grp::update (const Grp &, const SigmaI &, const Grp &, const SigmaI &)=0
	Gaussian likelihood, non-zero mean Gaussian prior. More...
virtual void	Grp::update (const Grp &, const Qgrp &, const SigmaI &, const Grp &, const SigmaI &)=0
	Student- \(t\) likelihood, non-zero mean Gaussian prior. More...
virtual void	Grp::update (const Grp &, const SigmaI &, const Grp &, const Qgrp &, const SigmaI &)=0
	Gaussian likelihood, non-zero mean Student- \(t\) prior. More...
virtual void	Grp::update (const Grp &, const Qgrp &, const SigmaI &, const Grp &, const Qgrp &, const SigmaI &)=0
	Student- \(t\) likelihood, non-zero mean Student- \(t\) prior. More...

Detailed Description

Function Documentation

update() [1/8]

virtual void MVnorm::update ( const Grp &  , const Qgrp &  , const SigmaI &  , const Grp &  , const double &  , const SigmaI &  , const gsl_rng *    )

pure virtual

Student- \(t\) likelihood, Student- \(t\) prior.

Parameters

[in]	Grp&	data for the likelihood
[in]	Qgrp&	vector Student- \(t\) covariance scale parameter for the likelihood covariance
[in]	SigmaI&	inverse-covariance matrix for the likelihood
[in]	Grp&	prior mean
[in]	double&	Student- \(t\) scale parameter for the prior covariance
[in]	SigmaI&	prior inverse-covariance matrix
[in]	gsl_rng*	pointer to a PNG

Implemented in MVnormBetaFt, MVnormMuBlk, MVnormBetaPEX, MVnormMuPEX, MVnormMu, MVnormBetaFtBlk, MVnormBetaBlk, and MVnormBeta.

update() [2/8]

virtual void Grp::update ( const Grp &  , const Qgrp &  , const SigmaI &  , const Grp &  , const Qgrp &  , const SigmaI &    )

pure virtual

Student- \(t\) likelihood, non-zero mean Student- \(t\) prior.

For the relationship to work properly, the _upLevel index of the focal object has to point to the rows of the prior mean matrix. This is the matrix addressed by dMat(). The relationship to the data is dependent on the derived class.

Parameters

[in]	Grp&	data
[in]	Qgrp&	Student- \(t\) weight parameter for the data
[in]	SigmaI&	data inverse-covariance
[in]	Grp&	prior mean
[in]	Qgrp&	Student- \(t\) weight parameter for the prior
[in]	SigmaI&	prior inverse-covariance

Implemented in MuBlk, BetaGrpPCpex, BetaGrpPEX, BetaGrpFt, MuGrpPEX, and MuGrp.

update() [3/8]

virtual void Grp::update ( const Grp &  , const Qgrp &  , const SigmaI &  , const Grp &  , const SigmaI &    )

pure virtual

Student- \(t\) likelihood, non-zero mean Gaussian prior.

For the relationship to work properly, the _upLevel index of the focal object has to point to the rows of the prior mean matrix. This is the matrix addressed by dMat(). The relationship to the data is dependent on the derived class.

Parameters

[in]	Grp&	data
[in]	Qgrp&	Student- \(t\) weight parameter for the data
[in]	SigmaI&	data inverse-covariance
[in]	Grp&	prior mean
[in]	SigmaI&	prior inverse-covariance

Implemented in MuBlk, BetaGrpPCpex, BetaGrpPEX, BetaGrpFt, MuGrpPEX, and MuGrp.

update() [4/8]

virtual void MVnorm::update ( const Grp &  , const Qgrp &  , const SigmaI &  , const Grp &  , const SigmaI &  , const gsl_rng *    )

pure virtual

Student- \(t\) likelihood, Gaussian prior.

Parameters

[in]	Grp&	data for the likelihood
[in]	Qgrp&	vector Student- \(t\) covariance scale parameter for the likelihood covariance
[in]	SigmaI&	inverse-covariance matrix for the likelihood
[in]	Grp&	prior mean
[in]	SigmaI&	prior inverse-covariance matrix
[in]	gsl_rng*	pointer to a PNG

Implemented in MVnormBetaFt, MVnormMuBlk, MVnormBetaPEX, MVnormMuPEX, MVnormMu, MVnormBetaFtBlk, MVnormBetaBlk, and MVnormBeta.

update() [5/8]

virtual void MVnorm::update ( const Grp &  , const SigmaI &  , const Grp &  , const double &  , const SigmaI &  , const gsl_rng *    )

pure virtual

Gaussian likelihood, Student- \(t\) prior.

Parameters

[in]	Grp&	data for the likelihood
[in]	SigmaI&	inverse-covariance matrix for the likelihood
[in]	Grp&	prior mean
[in]	double&	Student- \(t\) scale parameter for the prior covariance
[in]	SigmaI&	prior inverse-covariance matrix
[in]	gsl_rng*	pointer to a PNG

Implemented in MVnormBetaFt, MVnormMuBlk, MVnormBetaPEX, MVnormMuPEX, MVnormMu, MVnormBetaFtBlk, MVnormBetaBlk, and MVnormBeta.

update() [6/8]

virtual void Grp::update ( const Grp &  , const SigmaI &  , const Grp &  , const Qgrp &  , const SigmaI &    )

pure virtual

Gaussian likelihood, non-zero mean Student- \(t\) prior.

For the relationship to work properly, the _upLevel index of the focal object has to point to the rows of the prior mean matrix. This is the matrix addressed by dMat(). The relationship to the data is dependent on the derived class.

Parameters

[in]	Grp&	data
[in]	SigmaI&	data inverse-covariance
[in]	Grp&	prior mean
[in]	Qgrp&	Student- \(t\) weight parameter for the prior
[in]	SigmaI&	prior inverse-covariance

Implemented in MuBlk, BetaGrpPCpex, BetaGrpPEX, BetaGrpFt, MuGrpPEX, and MuGrp.

update() [7/8]

virtual void Grp::update ( const Grp &  , const SigmaI &  , const Grp &  , const SigmaI &    )

pure virtual

Gaussian likelihood, non-zero mean Gaussian prior.

For the relationship to work properly, the _upLevel index of the focal object has to point to the rows of the prior mean matrix. This is the matrix addressed by dMat(). The relationship to the data is dependent on the derived class.

Parameters

[in]	Grp&	data
[in]	SigmaI&	data inverse-covariance
[in]	Grp&	prior mean
[in]	SigmaI&	prior inverse-covariance

Implemented in MuBlk, BetaGrpPCpex, BetaGrpPEX, BetaGrpFt, MuGrpPEX, and MuGrp.

update() [8/8]

virtual void MVnorm::update ( const Grp &  , const SigmaI &  , const Grp &  , const SigmaI &  , const gsl_rng *    )

pure virtual

Gaussian likelihood, Gaussian prior.

Parameters

[in]	Grp&	data for the likelihood
[in]	SigmaI&	inverse-covariance matrix for the likelihood
[in]	Grp&	prior mean
[in]	SigmaI&	prior inverse-covariance matrix
[in]	gsl_rng*	pointer to a PNG

Implemented in MVnormBetaFt, MVnormMuBlk, MVnormBetaPEX, MVnormMuPEX, MVnormMu, MVnormBetaFtBlk, MVnormBetaBlk, and MVnormBeta.