Defines a class that constructs a likelihood object for a Nd gaussian distribution with diagonal covariance matrix. More...

#include "likelihood/likelihood_gaussian.h"

Inheritance diagram for likelihood_gaussian:

Collaboration diagram for likelihood_gaussian:

Public Member Functions
	likelihood_gaussian (std::vector< double > mean, std::vector< double > cov)

virtual double	operator() (std::vector< double > &x)
	Returns the log-likelihood of a vector of parameters \( \mathbf{x} \).

virtual double	chi_squared (std::vector< double > &x)
	Returns the \( \chi^2 \) of a vector of parameters \( \mathbf{x} \).

Public Member Functions inherited from likelihood_base
virtual std::vector< double >	gradient (std::vector< double > &x, prior &Pr)

virtual void	set_mpi_communicator (MPI_Comm comm)
	Defines a set of processors provided to the model for parallel computation via an MPI communicator. Only facilates code parallelization if the model computation is parallelized via MPI.

void	output_model_data_comparison (std::ostream &out)

void	output_model_data_comparison (std::string filename)

Additional Inherited Members
Protected Member Functions inherited from likelihood_base
virtual void	output (std::ostream &out)

Protected Attributes inherited from likelihood_base
MPI_Comm	_comm

Detailed Description

This class returns the log likelihood for a gaussian distribution of mean \( \mu \) and variance \( \sigma^{2} \)

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

Public Member Functions