hops: hops::ReversibleJumpProposal< MarkovChainImpl, Model > Class Template Reference

hops

#include <ReversibleJumpProposal.hpp>

Inheritance diagram for hops::ReversibleJumpProposal< MarkovChainImpl, Model >:

Inheritance graph

Collaboration diagram for hops::ReversibleJumpProposal< MarkovChainImpl, Model >:

Collaboration graph

Public Member Functions
	ReversibleJumpProposal (const MarkovChainImpl &markovChainImpl, const Model &model, Eigen::VectorXi m_jumpIndices, const typename MarkovChainImpl::StateType parameterDefaultValues)

void	draw (RandomNumberGenerator &randomNumberGenerator)

void	drawInModelSpace (RandomNumberGenerator &randomNumberGenerator, std::vector< int > &parameterActivationStates, typename MarkovChainImpl::StateType m_defaultValues)

void	drawInParameterSpace (RandomNumberGenerator &randomNumberGenerator)

double	computeParameterDrawAcceptanceProbability ()

double	getAcceptanceRate ()

MarkovChainImpl::StateType	getState ()

std::vector< std::string >	getParameterNames () const

Public Member Functions inherited from hops::Model
virtual	~Model ()=default

virtual MatrixType::Scalar	computeNegativeLogLikelihood (const VectorType &x) const =0
	Evaluates the negative log likelihood for input x. More...

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

virtual std::optional< MatrixType >	computeExpectedFisherInformation (const VectorType &) const

Constructor & Destructor Documentation

◆ ReversibleJumpProposal()

template<typename MarkovChainImpl , typename Model >

hops::ReversibleJumpProposal< MarkovChainImpl, Model >::ReversibleJumpProposal	(	const MarkovChainImpl &	markovChainImpl,
		const Model &	model,
		Eigen::VectorXi	m_jumpIndices,
		const typename MarkovChainImpl::StateType	parameterDefaultValues
	)

inline

Member Function Documentation

◆ computeParameterDrawAcceptanceProbability()

template<typename MarkovChainImpl , typename Model >

double hops::ReversibleJumpProposal< MarkovChainImpl, Model >::computeParameterDrawAcceptanceProbability ( )

inline

◆ draw()

template<typename MarkovChainImpl , typename Model >

void hops::ReversibleJumpProposal< MarkovChainImpl, Model >::draw ( RandomNumberGenerator & randomNumberGenerator )

inline

◆ drawInModelSpace()

template<typename MarkovChainImpl , typename Model >

void hops::ReversibleJumpProposal< MarkovChainImpl, Model >::drawInModelSpace	(	RandomNumberGenerator &	randomNumberGenerator,
		std::vector< int > &	parameterActivationStates,
		typename MarkovChainImpl::StateType	m_defaultValues
	)

inline

◆ drawInParameterSpace()

template<typename MarkovChainImpl , typename Model >

void hops::ReversibleJumpProposal< MarkovChainImpl, Model >::drawInParameterSpace ( RandomNumberGenerator & randomNumberGenerator )

inline

◆ getAcceptanceRate()

template<typename MarkovChainImpl , typename Model >

double hops::ReversibleJumpProposal< MarkovChainImpl, Model >::getAcceptanceRate ( )

inline

◆ getParameterNames()

template<typename MarkovChainImpl , typename Model >

std::vector<std::string> hops::ReversibleJumpProposal< MarkovChainImpl, Model >::getParameterNames ( ) const

inlinevirtual

Reimplemented from hops::Model.

◆ getState()

template<typename MarkovChainImpl , typename Model >

MarkovChainImpl::StateType hops::ReversibleJumpProposal< MarkovChainImpl, Model >::getState ( )

inline

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

ReversibleJumpProposal.hpp