Individual vector of regression coefficients with blocks of traits. More...

#include <MuGen.h>

Inheritance diagram for MVnormBetaBlk:

Collaboration diagram for MVnormBetaBlk:

Public Member Functions
	MVnormBetaBlk ()
	Default constructor. More...

	MVnormBetaBlk (const Grp &resp, gsl_matrix pred, const vector< size_t > &iCl, const gsl_matrix Sig, const vector< size_t > &blkStart, const gsl_rng r, gsl_matrix bet, const size_t &iRw)
	Constructor with no prior index. More...

	MVnormBetaBlk (const Grp &resp, gsl_matrix pred, const vector< size_t > &iCl, const gsl_matrix Sig, const vector< size_t > &blkStart, const gsl_rng r, const size_t &up, gsl_matrix bet, const size_t &iRw)
	Constructor with a prior index. More...

	MVnormBetaBlk (const gsl_matrix resp, gsl_matrix pred, const vector< size_t > &iCl, const gsl_matrix Sig, const vector< size_t > &blkStart, const gsl_rng r, gsl_matrix *bet, const size_t &iRw)
	Constructor with no prior index. More...

	MVnormBetaBlk (const gsl_matrix resp, gsl_matrix pred, const vector< size_t > &iCl, const gsl_matrix Sig, const vector< size_t > &blkStart, const gsl_rng r, const size_t &up, gsl_matrix *bet, const size_t &iRw)
	Constructor with a prior index. More...

virtual	~MVnormBetaBlk ()
	Destructor.

const size_t *	up () const
	Points to the prior. More...

virtual void	update (const Grp &dat, const SigmaI &SigIb, const gsl_rng *r)
	Gaussian likelihood. More...

virtual void	update (const Grp &dat, const Qgrp &q, const SigmaI &SigIb, const gsl_rng *r)
	Sudent- \(t\) likelihood. More...

virtual void	update (const Grp &dat, const SigmaI &SigIb, const SigmaI &SigIp, const gsl_rng *r)
	Gaussian likelihood, Gaussian prior. More...

virtual void	update (const Grp &dat, const SigmaI &SigIb, const double &qPr, const SigmaI &SigIp, const gsl_rng *r)
	Gaussian likelihood, Student- \(t\) prior. More...

virtual void	update (const Grp &dat, const Qgrp &q, const SigmaI &SigIb, const SigmaI &SigIp, const gsl_rng *r)
	Student- \(t\) likelihood, Gaussian prior. More...

virtual void	update (const Grp &dat, const Qgrp &q, const SigmaI &SigIb, const double &qPr, const SigmaI &SigIp, const gsl_rng *r)
	Student- \(t\) likelihood, Student- \(t\) prior. More...

virtual void	update (const Grp &dat, const SigmaI &SigIb, const Grp &muPr, const SigmaI &SigIp, const gsl_rng *r)
	Gaussian likelihood, Gaussian prior. More...

virtual void	update (const Grp &dat, const SigmaI &SigIb, const Grp &muPr, const double &qPr, const SigmaI &SigIp, const gsl_rng *r)
	Gaussian likelihood, Student- \(t\) prior. More...

virtual void	update (const Grp &dat, const Qgrp &q, const SigmaI &SigIb, const Grp &muPr, const SigmaI &SigIp, const gsl_rng *r)
	Student- \(t\) likelihood, Gaussian prior. More...

virtual void	update (const Grp &dat, const Qgrp &q, const SigmaI &SigIb, const Grp &muPr, const double &qPr, const SigmaI &SigIp, const gsl_rng *r)
	Student- \(t\) likelihood, Student- \(t\) prior. More...

Public Member Functions inherited from MVnorm
	MVnorm (const MVnorm &)
	Copy constructor. More...

MVnorm &	operator= (const MVnorm &)
	Assignement operator. More...

virtual	~MVnorm ()
	Virtual destructor. More...

virtual double	mhl (const MVnorm *x, const SigmaI &SigI)
	Mahalanobis distance to a vector. More...

virtual double	mhl (const MVnorm *x, const SigmaI &SigI) const
	Mahalanobis distance to a vector. More...

virtual double	mhl (const gsl_vector *x, const SigmaI &SigI)
	Mahalanobis distance to a vector. More...

virtual double	mhl (const gsl_vector *x, const SigmaI &SigI) const
	Mahalanobis distance to a vector. More...

virtual double	mhl (const SigmaI &SigI)
	Mahalanobis distance to zero. More...

virtual double	mhl (const SigmaI &SigI) const
	Mahalanobis distance to zero. More...

double	density (const gsl_vector *theta, const SigmaI &SigI)
	Multivariate Gaussian density. More...

double	density (const gsl_vector *theta, const SigmaI &SigI) const
	Multivariate Gaussian density. More...

double	density (const MVnorm *theta, const SigmaI &SigI)
	Multivariate Gaussian density. More...

double	density (const MVnorm *theta, const SigmaI &SigI) const
	Multivariate Gaussian density. More...

void	save (const string &fileNam, const char *how="a")
	Save function. More...

void	save (FILE *fileStr)
	Save function. More...

double	operator[] (const size_t i) const
	Subscript operator. More...

void	valSet (const size_t i, const double x)
	Setting an element to a value. More...

const gsl_vector *	getVec () const
	Access the location vector. More...

size_t	len () const
	Length of the location vector. More...

virtual size_t	nMissP () const
	Number of missing values. More...

virtual const vector< size_t >	getMisPhen () const
	Indexes of missing values. More...

virtual const vector< size_t > *	down () const
	Points to the corresponding data. More...

virtual double	scalePar () const
	Scale parameter. More...

Protected Attributes
const vector< size_t > *	_blkStart
	Start positions of blocks. More...

vector< gsl_vector_view >	_eachVec
	Trait blocks. More...

vector< gsl_vector_view >	_X
	Separate predictors. More...

vector< double >	_scale
	Vector of scales. More...

const size_t *	_upLevel
	Pointer to a row index of the prior. More...

Protected Attributes inherited from MVnorm
gsl_vector_view	_vec
	Data vector. More...

size_t	_d
	Length of the data vector.

Additional Inherited Members
Protected Member Functions inherited from MVnorm
	MVnorm ()
	Default constructor. More...

	MVnorm (const size_t &d)
	Dimension-only constructor. More...

	MVnorm (gsl_vector *mn)
	Dimension and vector value constructor. More...

	MVnorm (gsl_vector mn, const gsl_vector sd, const gsl_rng *r)
	Univariate Gaussian constructor. More...

	MVnorm (gsl_vector mn, const gsl_matrix Sig, const gsl_rng *r)
	Multivariate Gaussian constructor. More...

	MVnorm (gsl_matrix *mn, const size_t &iRw)
	Dimension and vector value constructor. More...

	MVnorm (gsl_matrix mn, const size_t &iRw, const gsl_vector sd, const gsl_rng *r)
	Univariate Gaussian constructor with a matrix. More...

	MVnorm (gsl_matrix mn, const size_t &iRw, const gsl_matrix Sig, const gsl_rng *r)
	Multivariate Gaussian constructor with a matrix. More...

Detailed Description

Individual vector of regression coefficients with blocks of traits.

Implements separate regression models for blocks of traits. The likelihood covariance matrix is block-diagonal. Traits of the same block have to be contiguous within the vector.

Constructor & Destructor Documentation

◆ MVnormBetaBlk() [1/5]

MVnormBetaBlk::MVnormBetaBlk ( )

inline

Default constructor.

Simply calls the MVnorm default constructor.

◆ MVnormBetaBlk() [2/5]

MVnormBetaBlk::MVnormBetaBlk	(	const Grp &	resp,
		gsl_matrix *	pred,
		const vector< size_t > &	iCl,
		const gsl_matrix *	Sig,
		const vector< size_t > &	blkStart,
		const gsl_rng *	r,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Constructor with no prior index.

Stochastic constructor for a regression with an improper prior.

Parameters

[in]	Grp&	response variable
[in]	gsl_matrix*	predictor matrix
[in]	vector<size_t>&	column indexes of the predictor matrix
[in]	gsl_matrix*	covariance marix for stochastic initiation
[in]	vector<size_t>&	vector of start indixes of each block
[in]	gsl_rng*	pointer to a PNG
[in]	gsl_matrix*	matrix of regression coefficients
[in]	size_t&	row index of the regression coefficient matrix

◆ MVnormBetaBlk() [3/5]

MVnormBetaBlk::MVnormBetaBlk	(	const Grp &	resp,
		gsl_matrix *	pred,
		const vector< size_t > &	iCl,
		const gsl_matrix *	Sig,
		const vector< size_t > &	blkStart,
		const gsl_rng *	r,
		const size_t &	up,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Constructor with a prior index.

Stochastic constructor for a regression with a proper prior.

Parameters

[in]	Grp&	response variable
[in]	gsl_matrix*	predictor matrix
[in]	vector<size_t>&	column indexes of the predictor matrix
[in]	gsl_matrix*	covariance marix for stochastic initiation
[in]	vector<size_t>&	vector of start indixes of each block
[in]	gsl_rng*	pointer to a PNG
[in]	size_t&	row index of the prior matrix
[in]	gsl_matrix*	matrix of regression coefficients
[in]	size_t&	row index of the regression coefficient matrix

◆ MVnormBetaBlk() [4/5]

MVnormBetaBlk::MVnormBetaBlk	(	const gsl_matrix *	resp,
		gsl_matrix *	pred,
		const vector< size_t > &	iCl,
		const gsl_matrix *	Sig,
		const vector< size_t > &	blkStart,
		const gsl_rng *	r,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Constructor with no prior index.

Stochastic constructor for a regression with an improper prior.

Parameters

[in]	gsl_matrix*	response matrix
[in]	gsl_matrix*	predictor matrix
[in]	vector<size_t>&	column indexes of the predictor matrix
[in]	gsl_matrix*	covariance marix for stochastic initiation
[in]	vector<size_t>&	vector of start indixes of each block
[in]	gsl_rng*	pointer to a PNG
[in]	gsl_matrix*	matrix of regression coefficients
[in]	size_t&	row index of the regression coefficient matrix

◆ MVnormBetaBlk() [5/5]

MVnormBetaBlk::MVnormBetaBlk	(	const gsl_matrix *	resp,
		gsl_matrix *	pred,
		const vector< size_t > &	iCl,
		const gsl_matrix *	Sig,
		const vector< size_t > &	blkStart,
		const gsl_rng *	r,
		const size_t &	up,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Constructor with a prior index.

Stochastic constructor for a regression with a proper prior.

Parameters

[in]	gsl_matrix*	response matrix
[in]	gsl_matrix*	predictor matrix
[in]	vector<size_t>&	column indexes of the predictor matrix
[in]	gsl_matrix*	covariance marix for stochastic initiation
[in]	vector<size_t>&	vector of start indixes of each block
[in]	gsl_rng*	pointer to a PNG
[in]	size_t&	row index of the prior matrix
[in]	gsl_matrix*	matrix of regression coefficients
[in]	size_t&	row index of the regression coefficient matrix

Member Function Documentation

◆ up()

const size_t* MVnormBetaBlk::up ( ) const

inlinevirtual

Points to the prior.

Access to the pointer to the correspoding vector of priors. Is non-zero only for classes where a prior is implemented.

Returns: Pointer to size_t.

Reimplemented from MVnorm.

◆ update() [1/10]

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

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

◆ update() [2/10]

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

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

◆ update() [3/10]

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

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

◆ update() [4/10]

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

virtual

Sudent- \(t\) likelihood.

Parameters

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

◆ update() [5/10]

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

virtual

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

Parameters

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

◆ update() [6/10]

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

virtual

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

Parameters

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

◆ update() [7/10]

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

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

◆ update() [8/10]

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

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

◆ update() [9/10]

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

virtual

Gaussian likelihood.

Parameters

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

◆ update() [10/10]

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

virtual

Gaussian likelihood, Gaussian prior.

Parameters

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

Implements MVnorm.

Reimplemented in MVnormBetaFtBlk.

Member Data Documentation

◆ _blkStart

const vector< size_t >* MVnormBetaBlk::_blkStart

protected

Start positions of blocks.

Pointer to the vector that's in the corresponding Grp class.

◆ _eachVec

vector< gsl_vector_view > MVnormBetaBlk::_eachVec

protected

Trait blocks.

Vector views of vector pieces, each corresponding to a block of variables. Pointer to the vector that's in the corresponding Grp class.

◆ _scale

vector<double> MVnormBetaBlk::_scale

protected

Vector of scales.

Typically \(X^{T}X\), but can bet something else in special cases. Each _X has a correspodning _scale.

◆ _upLevel

const size_t* MVnormBetaBlk::_upLevel

protected

Pointer to a row index of the prior.

This has to be the same for all the blocks.

◆ _X

vector< gsl_vector_view > MVnormBetaBlk::_X

protected

Separate predictors.

Vector views of predictor vectors, each corresponding to a block of variables. The predictor matrix is in the encompassing Grp class.

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

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ MVnormBetaBlk() [1/5]

◆ MVnormBetaBlk() [2/5]

◆ MVnormBetaBlk() [3/5]

◆ MVnormBetaBlk() [4/5]

◆ MVnormBetaBlk() [5/5]

Member Function Documentation

◆ up()

◆ update() [1/10]

◆ update() [2/10]

◆ update() [3/10]

◆ update() [4/10]

◆ update() [5/10]

◆ update() [6/10]

◆ update() [7/10]

◆ update() [8/10]

◆ update() [9/10]

◆ update() [10/10]

Member Data Documentation

◆ _blkStart

◆ _eachVec

◆ _scale

◆ _upLevel

◆ _X