hops::DegenerateMultivariateGaussian Class Reference

#include <DegenerateMultivariateGaussian.hpp>

Inheritance diagram for hops::DegenerateMultivariateGaussian:

Collaboration diagram for hops::DegenerateMultivariateGaussian:

Public Member Functions
	DegenerateMultivariateGaussian (VectorType mean, MatrixType covariance, std::vector< long > inactive=std::vector< long >(0))
MatrixType::Scalar	computeNegativeLogLikelihood (const VectorType &x) const override
	Evaluates the negative log likelihood for input x. More...
std::optional< VectorType >	computeLogLikelihoodGradient (const VectorType &x) const override
std::optional< MatrixType >	computeExpectedFisherInformation (const VectorType &) const override
Public Member Functions inherited from hops::Model
virtual	~Model ()=default
virtual std::optional< std::vector< std::string > >	getParameterNames () const

Constructor & Destructor Documentation

DegenerateMultivariateGaussian()

hops::DegenerateMultivariateGaussian::DegenerateMultivariateGaussian	(	VectorType	mean,
		MatrixType	covariance,
		std::vector< long >	inactive = std::vector<long>(0)
	)

Member Function Documentation

computeExpectedFisherInformation()

std::optional< MatrixType > hops::DegenerateMultivariateGaussian::computeExpectedFisherInformation ( const VectorType &  x ) const

overridevirtual

Reimplemented from hops::Model.

computeLogLikelihoodGradient()

std::optional< VectorType > hops::DegenerateMultivariateGaussian::computeLogLikelihoodGradient ( const VectorType &  x ) const

overridevirtual

Reimplemented from hops::Model.

computeNegativeLogLikelihood()

MatrixType::Scalar hops::DegenerateMultivariateGaussian::computeNegativeLogLikelihood ( const VectorType &  x ) const

overridevirtual

Evaluates the negative log likelihood for input x.

Parameters

x

Returns

Implements hops::Model.

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

• DegenerateMultivariateGaussian.hpp