Data with measurement error. More...

#include <MuGen.h>

Inheritance diagram for MuGrpEE:

Collaboration diagram for MuGrpEE:

Public Member Functions
	MuGrpEE ()
	Default constructor.

	MuGrpEE (const string &datFlNam, const string &varFlNam, const string &indFlNam, RanIndex &up, const size_t &d)
	Constructor with index read from a file. More...

	MuGrpEE (const string &datFlNam, const string &varFlNam, const vector< size_t > &varInd, RanIndex &up, const size_t &d)
	Constructor with index vector. More...

	~MuGrpEE ()
	Destructor.

	MuGrpEE (const MuGrpEE &mG)
	Copy constructor. More...

MuGrpEE &	operator= (const MuGrpEE &mG)
	Assignment operator. More...

virtual void	update (const Grp &muPr, const SigmaI &SigIm)
	Gaussian prior. More...

virtual void	update (const Grp &muPr, const Qgrp &q, const SigmaI &SigIm)
	Student- \(t\) prior. More...

Public Member Functions inherited from MuGrp
	MuGrp ()
	Default constructor.

	MuGrp (RanIndex &low, const size_t &d)
	Deterministic zero-value constructor. More...

	MuGrp (const string &datFlNam, RanIndex &low, RanIndex &up, const size_t &d)
	Constructor with data from file. More...

	MuGrp (const string &datFlNam, RanIndex &up, const size_t &d)
	Constructor with data from file and no lower level. More...

	MuGrp (const vector< MVnorm * > &dat, RanIndex &low, RanIndex &up)
	Constructor with a vector of MVnorm pointers. More...

	MuGrp (const Grp &dat, RanIndex &low, RanIndex &up)
	Constructor with a Grp object. More...

	MuGrp (const vector< MVnorm * > &dat, RanIndex &low, RanIndex &up, const string &outFlNam)
	Constructor with a vector of MVnorm pointers and output file name. More...

	MuGrp (const Grp &dat, RanIndex &low, RanIndex &up, const string &outFlNam)
	Constructor with a Grp object and output file name. More...

	MuGrp (const Grp &dat, RanIndex &low)
	Deterministic mean constructor. More...

	MuGrp (const Grp &dat, const Qgrp &q, RanIndex &low)
	Deterministic weighted mean constructor. More...

	MuGrp (const gsl_matrix *dat)
	Deterministic constructor with a GSL matrix. More...

	MuGrp (const gsl_matrix *dat, RanIndex &low)
	Deterministic GSL matrix mean constructor. More...

	MuGrp (const gsl_matrix *dat, const Qgrp &q, RanIndex &low)
	Deterministic GSL matrix weighted mean constructor. More...

virtual	~MuGrp ()
	Destructor.

	MuGrp (const MuGrp &mG)
	Copy constructor. More...

	MuGrp (const Grp &g)
	Copy constructor. More...

MuGrp &	operator= (const MuGrp &mG)
	Assignemnt operator. More...

virtual void	update (const Grp &dat, const SigmaI &SigIm, const SigmaI &SigIp)
	Gaussian likelihood, 0-mean Gaussian prior. More...

virtual void	update (const Grp &dat, const Qgrp &q, const SigmaI &SigIm, const SigmaI &SigIp)
	Student- \(t\) likelihood, 0-mean Gaussian prior. More...

virtual void	update (const Grp &dat, const SigmaI &SigIm, const Qgrp &qPr, const SigmaI &SigIp)
	Gaussian likelihood, 0-mean Student- \(t\) prior. More...

virtual void	update (const Grp &dat, const Qgrp &q, const SigmaI &SigIm, const Qgrp &qPr, const SigmaI &SigIp)
	Student- \(t\) likelihood, 0-mean Student- \(t\) prior. More...

virtual void	update (const Grp &dat, const SigmaI &SigIm, const Grp &muPr, const SigmaI &SigIp)
	Gaussian likelihood, non-zero mean Gaussian prior. More...

virtual void	update (const Grp &dat, const Qgrp &q, const SigmaI &SigIm, const Grp &muPr, const SigmaI &SigIp)
	Student- \(t\) likelihood, non-zero mean Gaussian prior. More...

virtual void	update (const Grp &dat, const SigmaI &SigIm, const Grp &muPr, const Qgrp &qPr, const SigmaI &SigIp)
	Gaussian likelihood, non-zero mean Student- \(t\) prior. More...

virtual void	update (const Grp &dat, const Qgrp &q, const SigmaI &SigIm, const Grp &muPr, const Qgrp &qPr, const SigmaI &SigIp)
	Student- \(t\) likelihood, non-zero mean Student- \(t\) prior. More...

Public Member Functions inherited from Grp
virtual	~Grp ()
	Destructor.

virtual void	save ()
	Save to pre-specified file. More...

virtual void	save (const string &outFlNam)
	Save to file. More...

virtual void	save (const string &outMuFlNam, const string &outSigFlNam, const SigmaI &SigI)
	Joint save. More...

virtual void	save (const SigmaI &SigI)
	Save with inverse-covariance. More...

virtual void	save (const Grp &y, const SigmaI &SigI)
	Save with data and inverse-covariance. More...

void	mhlSave (const string &outFlNam, const SigmaI SigI)
	Save Mahalanobis distance. More...

virtual void	dump ()
	Dump to a file. More...

const vector< MVnorm * > &	dataVec () const
	Get vector of row pointers. More...

virtual const gsl_matrix *	dMat () const
	Access the value matrix. More...

virtual const gsl_matrix *	fMat () const
	Access the value matrix. More...

const size_t	Ndata () const
	Get number of rows. More...

const size_t	phenD () const
	Get number of traits. More...

virtual double	lnOddsRat (const Grp &y, const SigmaI &SigI, const size_t i) const
	Log-odds ratio. More...

const MVnorm *	operator[] (const size_t i) const
	Subscript operator. More...

MVnorm *	operator[] (const size_t i)
	Subscript operator. More...

virtual MuGrp	mean (RanIndex &grp)
	Group mean. More...

virtual const MuGrp	mean (RanIndex &grp) const
	Group mean. More...

virtual MuGrp	mean (RanIndex &grp, const Qgrp &q)
	Group weighted mean. More...

virtual const MuGrp	mean (RanIndex &grp, const Qgrp &q) const
	Group weighted mean. More...

void	center ()
	Center the value matrix. More...

Protected Attributes
gsl_matrix *	_errorInvVar
	Matrix of error inverse-variances. More...

gsl_matrix *	_meanVal
	Matrix of means. More...

vector< size_t >	_errInd
	Trait index. More...

Protected Attributes inherited from Grp
vector< MVnorm * >	_theta
	Vector of pointers to value rows. More...

gsl_matrix *	_valueMat
	Value matrix. More...

RanIndex *	_lowLevel
	Lower level index. More...

RanIndex *	_upLevel
	Upper level index. More...

vector< gsl_rng * >	_rV
	Vector of PNG pointers. More...

string	_outFlNam
	Name of the output file.

Additional Inherited Members
Protected Member Functions inherited from Grp
	Grp ()

Detailed Description

Data with measurement error.

If some phenotypes are measured with known error (e.g., technical replicates that are not idividually available), these can be sampled rather than used as point estimates. A mix of traits with and without measurement error is allowed. This class has to be on the bottom of the model hierarchy.

Constructor & Destructor Documentation

◆ MuGrpEE() [1/3]

MuGrpEE::MuGrpEE	(	const string &	datFlNam,
		const string &	varFlNam,
		const string &	indFlNam,
		RanIndex &	up,
		const size_t &	d
	)

Constructor with index read from a file.

The data, error variances and the index identifying traits with errors are read from files. The index file must be a white-space separated text file. Variances are inverted after reading and are checked for sanity (i.e. not smaller than machine epsilon).

Parameters

[in]	string&	data file name
[in]	string&	variance file name
[in]	string&	index values file name
[in]	RainIndex&	upper level (prior) index
[in]	size_t&	number of traits

◆ MuGrpEE() [2/3]

MuGrpEE::MuGrpEE	(	const string &	datFlNam,
		const string &	varFlNam,
		const vector< size_t > &	varInd,
		RanIndex &	up,
		const size_t &	d
	)

Constructor with index vector.

The data and error variances are read from files, but the index identifying traits with errors is provided in a vector. Variances are inverted after reading and are checked for sanity (i.e. not smaller than machine epsilon).

Parameters

[in]	string&	data file name
[in]	string&	variance file name
[in]	vector<size_t>&	index values file name
[in]	RainIndex&	upper level (prior) index
[in]	size_t&	number of traits

◆ MuGrpEE() [3/3]

MuGrpEE::MuGrpEE ( const MuGrpEE & mG )

Copy constructor.

Parameters

[in] MuGrpEE& object to be copied

Returns: MuGrpEE object

Member Function Documentation

◆ operator=()

MuGrpEE & MuGrpEE::operator= ( const MuGrpEE & mG )

Assignment operator.

Parameters

[in] MuGrpEE& object to be copied

Returns: MuGrpEE& target object

Member Data Documentation

◆ _errInd

vector<size_t> MuGrpEE::_errInd

protected

Trait index.

Contains indexes of the traits that have measurment errors. Only one index for all rows, i.e. once a trait has measurment error all samples must have a non-zero error variance.

◆ _errorInvVar

gsl_matrix* MuGrpEE::_errorInvVar

protected

Matrix of error inverse-variances.

The matrix has the same number of rows as the value matrix, and the number of columns no larger than the value matrix. Variances are read from a file and inverted on initialization.

◆ _meanVal

gsl_matrix* MuGrpEE::_meanVal

protected

Matrix of means.

Has the same dimensions as the _errorVar matrix, and stores mean values for the variables that will be sampled.

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

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ MuGrpEE() [1/3]

◆ MuGrpEE() [2/3]

◆ MuGrpEE() [3/3]

Member Function Documentation

◆ operator=()

Member Data Documentation

◆ _errInd

◆ _errorInvVar

◆ _meanVal