A class that represents a Gaussian likelihood with full covariance. More...

#include <GaussianLikelihoodFullCovariance.h>

Inheritance diagram for QUESO::GaussianLikelihoodFullCovariance< V, M >:

Public Member Functions
virtual double	lnValue (const V &domainVector) const
	Logarithm of the value of the scalar function. More...

Constructor/Destructor methods.
	GaussianLikelihoodFullCovariance (const char *prefix, const VectorSet< V, M > &domainSet, const V &observations, const M &covariance, double covarianceCoefficient=1.0)
	Default constructor. More...

virtual	~GaussianLikelihoodFullCovariance ()
	Destructor. More...

Public Member Functions inherited from QUESO::LikelihoodBase< V, M >
virtual void	evaluateModel (const V &domainVector, const V domainDirection, V &modelOutput, V gradVector, M hessianMatrix, V hessianEffect) const
	Deprecated. Evaluates the user's model at the point `domainVector`. More...

virtual void	evaluateModel (const V &domainVector, V &modelOutput) const
	Evaluates the user's model at the point `domainVector`. More...

virtual double	actualValue (const V &domainVector, const V , V , M , V ) const
	Actual value of the scalar function. More...

	LikelihoodBase (const char *prefix, const VectorSet< V, M > &domainSet, const V &observations)
	Default constructor. More...

virtual	~LikelihoodBase ()=0
	Destructor, pure to make this class abstract. More...

Public Member Functions inherited from QUESO::BaseScalarFunction< V, M >
void	setFiniteDifferenceStepSize (double fdStepSize)
	Sets the step size for finite differencing gradients. More...

void	setFiniteDifferenceStepSize (unsigned int i, double fdStepSize)

	BaseScalarFunction (const char *prefix, const VectorSet< V, M > &domainSet)
	Default constructor. More...

virtual	~BaseScalarFunction ()
	Destructor. More...

const VectorSet< V, M > &	domainSet () const
	Access to the protected attribute `m_domainSet:` domain set of the scalar function. More...

virtual double	lnValue (const V &domainVector, const V domainDirection, V gradVector, M hessianMatrix, V hessianEffect) const
	Logarithm of the value of the scalar function. Deprecated. More...

virtual double	lnValue (const V &domainVector, V &gradVector) const
	Returns the logarithm of the function and its gradient at `domainVector`. More...

virtual double	lnValue (const V &domainVector, V &gradVector, const V &domainDirection, V &hessianEffect) const

Private Attributes
double	m_covarianceCoefficient

const M &	m_covariance

Additional Inherited Members
Protected Attributes inherited from QUESO::LikelihoodBase< V, M >
const V &	m_observations

Protected Attributes inherited from QUESO::BaseScalarFunction< V, M >
const BaseEnvironment &	m_env

std::string	m_prefix

const VectorSet< V, M > &	m_domainSet
	Domain set of the scalar function. More...

Detailed Description

template<class V = GslVector, class M = GslMatrix>
class QUESO::GaussianLikelihoodFullCovariance< V, M >

A class that represents a Gaussian likelihood with full covariance.

Definition at line 43 of file GaussianLikelihoodFullCovariance.h.

Constructor & Destructor Documentation

template<class V , class M >

QUESO::GaussianLikelihoodFullCovariance< V, M >::GaussianLikelihoodFullCovariance	(	const char *	prefix,
		const VectorSet< V, M > &	domainSet,
		const V &	observations,
		const M &	covariance,
		double	covarianceCoefficient = `1.0`
	)

Default constructor.

Instantiates a Gaussian likelihood function, given a prefix, its domain, a set of observations and a full covariance matrix. The full covariance matrix is stored as a matrix in the covariance parameter.

The parameter covarianceCoefficient is a multiplying factor of covaraince and is fixed (i.e. not solved for in a statistical inversion).

Definition at line 35 of file GaussianLikelihoodFullCovariance.C.

   : LikelihoodBase<V, M>(prefix, domainSet, observations),
     m_covarianceCoefficient(covarianceCoefficient),
     m_covariance(covariance)
 {
   if (covariance.numRowsLocal() != observations.sizeLocal()) {
     queso_error_msg("Covariance matrix not same size as observation vector");
   }
 }

template<class V , class M >

QUESO::GaussianLikelihoodFullCovariance< V, M >::~GaussianLikelihoodFullCovariance ( )

virtual

Destructor.

Definition at line 48 of file GaussianLikelihoodFullCovariance.C.

49 {

50 }

Member Function Documentation

template<class V , class M >

double QUESO::GaussianLikelihoodFullCovariance< V, M >::lnValue ( const V & domainVector ) const

virtual

Logarithm of the value of the scalar function.

Reimplemented from QUESO::BaseScalarFunction< V, M >.

Definition at line 54 of file GaussianLikelihoodFullCovariance.C.

 {
   V modelOutput(this->m_observations, 0, 0);  // At least it's not a copy
   V weightedMisfit(this->m_observations, 0, 0);  // At least it's not a copy
 
   this->evaluateModel(domainVector, modelOutput);
 
   // Compute misfit G(x) - y
   modelOutput -= this->m_observations;
 
   // Solve \Sigma u = G(x) - y for u
   this->m_covariance.invertMultiply(modelOutput, weightedMisfit);
 
   // Compute (G(x) - y)^T \Sigma^{-1} (G(x) - y)
   modelOutput *= weightedMisfit;
 
   // This is square of 2-norm
   double norm2_squared = modelOutput.sumOfComponents();
 
   return -0.5 * norm2_squared / (this->m_covarianceCoefficient);
 }