Generic regression. More...

#include <MuGen.h>

Inheritance diagram for MVnormBeta:

Collaboration diagram for MVnormBeta:

Public Member Functions
	MVnormBeta ()
	Default constructor.

	MVnormBeta (const size_t d)
	Dimension-only constructor. More...

	MVnormBeta (gsl_vector b, const gsl_vector sd, gsl_matrix pred, const size_t &iCl, const gsl_rng r)
	Univariate random constructor with vector. More...

	MVnormBeta (gsl_vector b, const gsl_vector sd, gsl_matrix pred, const size_t &iCl, const gsl_rng r, const size_t &up)
	Univariate random constructor with vector and pointer to prior. More...

	MVnormBeta (gsl_vector b, const gsl_matrix Sig, gsl_matrix pred, const size_t &iCl, const gsl_rng r)
	Multivariate random constructor with vector. More...

	MVnormBeta (gsl_vector b, const gsl_matrix Sig, gsl_matrix pred, const size_t &iCl, const gsl_rng r, const size_t &up)
	Multivariate random constructor with vector and pointer to prior. More...

	MVnormBeta (const gsl_matrix resp, gsl_matrix pred, const size_t &iCl, const gsl_matrix Sig, const gsl_rng r, gsl_matrix *bet, const size_t &iRw)
	Multivariate constructor with response matrix. More...

	MVnormBeta (const gsl_matrix resp, gsl_matrix pred, const size_t &iCl, const gsl_matrix Sig, const gsl_rng r, const size_t &up, gsl_matrix *bet, const size_t &iRw)
	Multivariate constructor with response matrix and index for a prior. More...

	MVnormBeta (const Grp &resp, gsl_matrix pred, const size_t &iCl, const gsl_matrix Sig, const gsl_rng r, gsl_matrix bet, const size_t &iRw)
	Multivariate constructor with a Grp type response. More...

	MVnormBeta (const Grp &resp, gsl_matrix pred, const size_t &iCl, const gsl_matrix Sig, const gsl_rng r, const size_t &up, gsl_matrix bet, const size_t &iRw)
	Multivariate constructor with a Grp type response and index for a prior. More...

	MVnormBeta (gsl_matrix pred, const size_t &iCl, gsl_matrix bet, const size_t &iRw)
	Deterministic constructor. More...

	MVnormBeta (gsl_matrix pred, const size_t &iCl, const size_t &up, gsl_matrix bet, const size_t &iRw)
	Deterministic constructor with prior index. More...

	MVnormBeta (const MVnormBeta &)
	Deterministic copy constructor. More...

MVnormBeta &	operator= (const MVnormBeta &)
	Deterministic assignement operator. More...

virtual	~MVnormBeta ()
	Destructor.

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...

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

double	scalePar () const
	Scale parameter. 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...

Protected Attributes
gsl_vector_view	_X
	Predictor. More...

double	_scale
	Scale parameter. More...

size_t	_N
	Length of the predictor.

const size_t *	_upLevel
	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

Generic regression.

Generic implementation of a regression. By itself to be used strictly for regressions with a single predictor because it ignores the effects of other predictors.

Constructor & Destructor Documentation

◆ MVnormBeta() [1/12]

MVnormBeta::MVnormBeta ( const size_t d )

Dimension-only constructor.

Sets the dimension to a value, but the _vec is not assigned a target.

◆ MVnormBeta() [2/12]

MVnormBeta::MVnormBeta	(	gsl_vector *	b,
		const gsl_vector *	sd,
		gsl_matrix *	pred,
		const size_t &	iCl,
		const gsl_rng *	r
	)

Univariate random constructor with vector.

Sets up _vec to point to the provided vector of values, and the predictor to a column in the provided matrix of predictors.

Parameters

[in]	gsl_vector*	vector of values
[in]	gsl_vector*	vector of standard deviations
[in]	gsl_matrix*	matrix of predictors
[in]	size_t&	column index for the predictor matrix
[in]	gsl_rng*	pointer to a PNG

◆ MVnormBeta() [3/12]

MVnormBeta::MVnormBeta	(	gsl_vector *	b,
		const gsl_vector *	sd,
		gsl_matrix *	pred,
		const size_t &	iCl,
		const gsl_rng *	r,
		const size_t &	up
	)

Univariate random constructor with vector and pointer to prior.

Sets up _vec to point to the provided vector of values, the predictor to a column in the provided matrix of predictors, and the pointer to the corresponding row in the prior matrix.

Parameters

[in]	gsl_vector*	vector of values
[in]	gsl_vector*	vector of standard deviations
[in]	gsl_matrix*	matrix of predictors
[in]	size_t&	column index for the predictor matrix
[in]	gsl_rng*	pointer to a PNG
[in]	size_t&	index of the appropriate row in the prior matrix

◆ MVnormBeta() [4/12]

MVnormBeta::MVnormBeta	(	gsl_vector *	b,
		const gsl_matrix *	Sig,
		gsl_matrix *	pred,
		const size_t &	iCl,
		const gsl_rng *	r
	)

Multivariate random constructor with vector.

Sets up _vec to point to the provided vector of values, and the predictor to a column in the provided matrix of predictors.

Parameters

[in]	gsl_vector*	vector of values
[in]	gsl_matrix*	covariance matrix
[in]	gsl_matrix*	matrix of predictors
[in]	size_t&	column index for the predictor matrix
[in]	gsl_rng*	pointer to a PNG

◆ MVnormBeta() [5/12]

MVnormBeta::MVnormBeta	(	gsl_vector *	b,
		const gsl_matrix *	Sig,
		gsl_matrix *	pred,
		const size_t &	iCl,
		const gsl_rng *	r,
		const size_t &	up
	)

Multivariate random constructor with vector and pointer to prior.

Sets up _vec to point to the provided vector of values, the predictor to a column in the provided matrix of predictors, and the pointer to the corresponding row in the prior matrix.

Parameters

[in]	gsl_vector*	vector of values
[in]	gsl_matrix*	covariance matrix
[in]	gsl_matrix*	matrix of predictors
[in]	size_t&	column index for the predictor matrix
[in]	gsl_rng*	pointer to a PNG
[in]	size_t&	index of the appropriate row in the prior matrix

◆ MVnormBeta() [6/12]

MVnormBeta::MVnormBeta	(	const gsl_matrix *	resp,
		gsl_matrix *	pred,
		const size_t &	iCl,
		const gsl_matrix *	Sig,
		const gsl_rng *	r,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Multivariate constructor with response matrix.

Sets up _vec to point to a row in the provided matrix of regression coefficients, and the predictor to a column of the matrix of predictors. Initializes regression coefficients using the provided response matrix.

Parameters

[in]	gsl_matrix*	response matrix
[in]	gsl_matrix*	predictor martix
[in]	size_t&	column index of the predictor matrix
[in]	gsl_matrix*	covariance matrix
[in]	gsl_rng*	pointer to a PNG
[in]	gsl_matrix*	matrix of regression coefficients
[in]	size_t&	row index of the regression coefficient matrix

◆ MVnormBeta() [7/12]

MVnormBeta::MVnormBeta	(	const gsl_matrix *	resp,
		gsl_matrix *	pred,
		const size_t &	iCl,
		const gsl_matrix *	Sig,
		const gsl_rng *	r,
		const size_t &	up,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Multivariate constructor with response matrix and index for a prior.

Sets up _vec to point to a row in the provided matrix of regression coefficients, and the predictor to a column of the matrix of predictors. Initializes regression coefficients using the provided response matrix.
Initializes _upLevel to point to the appropriate row in the matrix of priors.

Parameters

[in]	gsl_matrix*	response matrix
[in]	gsl_matrix*	predictor martix
[in]	size_t&	column index of the predictor matrix
[in]	gsl_matrix*	covariance matrix
[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

◆ MVnormBeta() [8/12]

MVnormBeta::MVnormBeta	(	const Grp &	resp,
		gsl_matrix *	pred,
		const size_t &	iCl,
		const gsl_matrix *	Sig,
		const gsl_rng *	r,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Multivariate constructor with a Grp type response.

Sets up _vec to point to a row in the provided matrix of regression coefficients, and the predictor to a column of the matrix of predictors. Initializes regression coefficients using the provided response matrix.

Parameters

[in]	Grp&	response
[in]	gsl_matrix*	predictor martix
[in]	size_t&	column index of the predictor matrix
[in]	gsl_matrix*	covariance matrix
[in]	gsl_rng*	pointer to a PNG
[in]	gsl_matrix*	matrix of regression coefficients
[in]	size_t&	row index of the regression coefficient matrix

◆ MVnormBeta() [9/12]

MVnormBeta::MVnormBeta	(	const Grp &	resp,
		gsl_matrix *	pred,
		const size_t &	iCl,
		const gsl_matrix *	Sig,
		const gsl_rng *	r,
		const size_t &	up,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Multivariate constructor with a Grp type response and index for a prior.

Sets up _vec to point to a row in the provided matrix of regression coefficients, and the predictor to a column of the matrix of predictors. Initializes regression coefficients using the provided response matrix. Initializes _upLevel to point to the appropriate row in the matrix of priors.

Parameters

[in]	Grp&	response
[in]	gsl_matrix*	predictor martix
[in]	size_t&	column index of the predictor matrix
[in]	gsl_matrix*	covariance matrix
[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

◆ MVnormBeta() [10/12]

MVnormBeta::MVnormBeta	(	gsl_matrix *	pred,
		const size_t &	iCl,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Deterministic constructor.

Does not initialize the regression coefficients, but simply points to the already-initialized matrix of values.

Parameters

[in]	gsl_matrix*	predictor matrix
[in]	size_t&	column index of the predictor matrix
[in]	gsl_matrix*	regression coefficient matrix
[in]	size_t&	row index of the regression coefficient matrix

◆ MVnormBeta() [11/12]

MVnormBeta::MVnormBeta	(	gsl_matrix *	pred,
		const size_t &	iCl,
		const size_t &	up,
		gsl_matrix *	bet,
		const size_t &	iRw
	)

Deterministic constructor with prior index.

Does not initialize the regression coefficients, but simply points to the already-initialized matrix of values. Sets the _upLevel to point to the corresponding row of the prior matrix

Parameters

[in]	gsl_matrix*	predictor matrix
[in]	size_t&	column index of the predictor matrix
[in]	size_t&	row index of the prior matrix
[in]	gsl_matrix*	regression coefficient matrix
[in]	size_t&	row index of the regression coefficient matrix

◆ MVnormBeta() [12/12]

MVnormBeta::MVnormBeta ( const MVnormBeta & b )

Deterministic copy constructor.

Parameters

[in] MVnormBeta& object to be copied

Member Function Documentation

◆ operator=()

MVnormBeta & MVnormBeta::operator= ( const MVnormBeta & b )

Deterministic assignement operator.

Parameters

[in] MVnormBeta& object to be assigned

Returns: A reference to a MVnormBeta object

◆ scalePar()

double MVnormBeta::scalePar ( ) const

inlinevirtual

Scale parameter.

Access to a scale parameter member, defined only for some derived regression-type classes. If not defined, returns 1.0.

Returns: Scale paramter value of type double.

Reimplemented from MVnorm.

◆ up()

const size_t* MVnormBeta::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 MVnormBeta::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 MVnormBetaFt.

◆ update() [2/10]

void MVnormBeta::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 MVnormBetaFt.

◆ update() [3/10]

void MVnormBeta::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 MVnormBetaFt.

◆ update() [4/10]

void MVnormBeta::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 MVnormBetaFt.

◆ update() [5/10]

void MVnormBeta::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 MVnormBetaFt.

◆ update() [6/10]

void MVnormBeta::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 MVnormBetaFt.

◆ update() [7/10]

void MVnormBeta::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 MVnormBetaFt.

◆ update() [8/10]

void MVnormBeta::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 MVnormBetaFt.

◆ update() [9/10]

void MVnormBeta::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 MVnormBetaFt.

◆ update() [10/10]

void MVnormBeta::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 MVnormBetaFt.

Member Data Documentation

◆ _scale

double MVnormBeta::_scale

protected

Scale parameter.

Typically \( x^{\textsc{t}}x \), but some exceptions exist in special cases.

◆ _upLevel

const size_t* MVnormBeta::_upLevel

protected

Row index of the prior.

Points to the index of a row in the prior matrix

◆ _X

gsl_vector_view MVnormBeta::_X

protected

Predictor.

Points to a vector of predictor values, typically a column of the predictor matrix that is in the encapsulating 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

◆ MVnormBeta() [1/12]

◆ MVnormBeta() [2/12]

◆ MVnormBeta() [3/12]

◆ MVnormBeta() [4/12]

◆ MVnormBeta() [5/12]

◆ MVnormBeta() [6/12]

◆ MVnormBeta() [7/12]

◆ MVnormBeta() [8/12]

◆ MVnormBeta() [9/12]

◆ MVnormBeta() [10/12]

◆ MVnormBeta() [11/12]

◆ MVnormBeta() [12/12]

Member Function Documentation

◆ operator=()

◆ scalePar()

◆ 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

◆ _scale

◆ _upLevel

◆ _X