Emrys::FilterBranch< MeasurementSpace, Scalar > Struct Template Reference

One branch of a filter's update (see FilterUpdate): its weight, its innovation, and its labels, without the posterior, which the filter reduced into its state (decisions.md [innovation-statistics]). More...

#include <EmrysFilter/Models/MeasurementUpdate.h>

Public Member Functions
Scalar	logLikelihood () const
Scalar	nis () const

Public Attributes
Scalar	logWeight
	log of its posterior probability among the branches of one update
Innovation< MeasurementSpace, Scalar >	innovation
	the observation's residual under it and its covariance
Eigen::Index	mode = 0
	flat index of the mode's discrete value, as UpdateBranch::mode
Eigen::Index	component
	index of the noise component, such as inlier or outlier
std::size_t	iterations = 1
	the linearizations made, as UpdateBranch::iterations
bool	converged = true
	as UpdateBranch::converged

Detailed Description

template<typename MeasurementSpace, typename Scalar = double>
struct Emrys::FilterBranch< MeasurementSpace, Scalar >

One branch of a filter's update (see FilterUpdate): its weight, its innovation, and its labels, without the posterior, which the filter reduced into its state (decisions.md [innovation-statistics]).

Template Parameters

MeasurementSpace

the measurement space

Member Function Documentation

logLikelihood()

template<typename MeasurementSpace, typename Scalar = double>

Scalar Emrys::FilterBranch< MeasurementSpace, Scalar >::logLikelihood ( ) const

inlinenodiscard

Returns

the log-likelihood of the observation under this branch

nis()

template<typename MeasurementSpace, typename Scalar = double>

Scalar Emrys::FilterBranch< MeasurementSpace, Scalar >::nis ( ) const

inlinenodiscard

Returns

the normalized innovation squared (see Innovation::nis())

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

• EmrysFilter/Models/MeasurementUpdate.h