bge_posterior.c File Reference

Describes a set of functions used for computing the posterior matrix of a continuous data set. More...

#include <stdio.h>
#include <string.h>
#include <assert.h>
#include "bge_posterior.h"

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Functions
void	SetPosteriorParametricMatrix (Bge_Matrix *data, Bge_Matrix *prior_matrix, Bge_Matrix *posterior_matrix, int alpha_mu, int alpha_omega)
	Sets the posterior matrix of the normal wishart disturbution over precision matrix W and mean v. More...
void	SetPriorParametricMatrix (int n, int alpha_mu, int alpha_omega, Bge_Matrix *prior_matrix)
	Defines the Prior matrix for the Wishart disturbution over precision matrix W. More...
void	SetSampleMean (Bge_Matrix *data, Bge_Vector *mean_vec)
	Finds the sample mean of the given data. More...
void	SetSampleVariance (Bge_Matrix *data, Bge_Vector *mean_vec, Bge_Matrix *variance_matrix)
	Finds the Sample Variance (multiplied by N-1) of a set of data. More...

Detailed Description

Describes a set of functions used for computing the posterior matrix of a continuous data set.

Function Documentation

SetPosteriorParametricMatrix()

void SetPosteriorParametricMatrix	(	Bge_Matrix *	data,
		Bge_Matrix *	prior_matrix,
		Bge_Matrix *	posterior_matrix,
		int	alpha_mu,
		int	alpha_omega
	)

Sets the posterior matrix of the normal wishart disturbution over precision matrix W and mean v.

Parameters

data	the problem data set
the	prior matrix for the wishart disturbution over the precision matrix W
posterior_matrix	the posterior matrix that is set for the normal wishart joint disturbution over the precision matrix and mean

References BgeMatrixAddition(), BgeMatrixCreate(), BgeMatrixDelete(), BgeMatrixScalarMultipliciation(), BgeVectorCreate(), BgeVectorDelete(), BgeVectorOuterProduct(), SetPriorParametricMatrix(), SetSampleMean(), and SetSampleVariance().

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SetPriorParametricMatrix()

void SetPriorParametricMatrix	(	int	n,
		int	alpha_mu,
		int	alpha_omega,
		Bge_Matrix *	prior_matrix
	)

Defines the Prior matrix for the Wishart disturbution over precision matrix W.

Parameters

n	the number of variables in the gaussian network
alpha_mu	hyper parameter for the wishart disturbution (normally set to 1)
alpha_omega	hyper parameter for the wishart disturbution (normally set to n + 2)
prior_matrix	prior matrix T for the wishart disturbtion over precision matrix W (dimensions = n * n)

Referenced by SetPosteriorParametricMatrix().

SetSampleMean()

void SetSampleMean	(	Bge_Matrix *	data,
		Bge_Vector *	mean_vec
	)

Finds the sample mean of the given data.

Parameters

data	the sample data used to calculate the mean
mean_vec	the output mean vector (capacity = data->cols)

References Bge_Vector::items.

Referenced by SetPosteriorParametricMatrix().

SetSampleVariance()

void SetSampleVariance	(	Bge_Matrix *	data,
		Bge_Vector *	mean_vec,
		Bge_Matrix *	variance_matrix
	)

Finds the Sample Variance (multiplied by N-1) of a set of data.

Parameters

data	the data set for the problem where rows = samples and cols = vars
mean_vec	the vector containing the means for each variable
variance_matrix	the output variance matrix (dimensions = data->cols * data->cols)

References BgeMatrixAddition(), BgeMatrixCreate(), BgeMatrixDelete(), BgeVectorCreate(), BgeVectorDelete(), BgeVectorOuterProduct(), BgeVectorSubtraction(), and Bge_Vector::items.

Referenced by SetPosteriorParametricMatrix().

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