Defines the Lorentzian likelihood. More...

#include "likelihood/likelihood_cauchy.h"

Inheritance diagram for likelihood_cauchy:

Collaboration diagram for likelihood_cauchy:

Public Member Functions
	likelihood_cauchy (double mean, double alpha)

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 \( \mathbf{x} \).

virtual void	set_mpi_communicator (MPI_Comm comm)
	Defines a set of processors provided to the likelihood for parallel computation via an MPI communicator.

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

void	output_model_data_comparison (std::ostream &out)

void	output_model_data_comparison (std::string filename)

Private Attributes
double	_m

double	_alpha

MPI_Comm	_comm

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

Defines a multi-dimensional Lorentzian likelihood as a test example for the sampler routines. This likelihood consists of multiple well separated sharp modes and thus makes for a challenging sampling problem

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

likelihood/likelihood_cauchy.h

Public Member Functions

Private Attributes

Additional Inherited Members

Detailed Description