NAME

compute_gaussian_process_likelihood_i - Computes the likelihood of a GP the data given parameters

SYNOPSIS

#include "gp/gp_gaussian_processes.h"

Example compile flags (system dependent):
  -DLINUX_X86_64 -DLINUX_X86_64_OPTERON  -DGNU_COMPILER 
   -I/home/kobus/include
   -L/home/kobus/misc/load/linux_x86_64_opteron -L/usr/lib/x86_64-linux-gnu
  -lKJB                               -lfftw3  -lgsl -lgslcblas -ljpeg  -lSVM -lstdc++                    -lpthread -lSLATEC -lg2c    -lacml -lacml_mv -lblas -lg2c      -lncursesw 


int compute_gaussian_process_likelihood_i
(
	double *density,
	const Vector_vector *train_data,
	const Vector_vector *function_values,
	double noise_sigma
);

DESCRIPTION

This routine computes the likelihood of the data given the parameters. In the context of Gaussian processes, this means computing the likelihood of the training data (train_data) give some function values (function_values) at time points train_indices. noise_sigma is the variance of the noise process. This routine assumes that the dimensions of the data are (statistically) independent.

RETURNS

If the routine fails (due to storage allocation, an error in the covariance function, or a mismatch in the sizes of the indices), then ERROR is returned with and error message being set. Otherwise NO_ERROR is returned.

DISCLAIMER

This software is not adequatedly tested. It is recomended that results are checked independantly where appropriate.

AUTHOR

Ernesto Brau

DOCUMENTER

Ernesto Brau

SEE ALSO

fill_covariance_matrix , fill_mean_vector , sample_from_gaussian_process_prior , sample_from_gaussian_process_prior_i , sample_from_gaussian_process_predictive , sample_from_gaussian_process_predictive_i , get_gaussian_process_predictive_distribution , get_gaussian_process_predictive_distribution_i , get_gaussian_process_posterior_distribution , get_gaussian_process_posterior_distribution_i , compute_gaussian_process_likelihood , compute_gaussian_process_marginal_likelihood , compute_gaussian_process_marginal_likelihood_i , compute_gaussian_process_marginal_log_likelihood , compute_gaussian_process_marginal_log_likelihood_i