Detailed Description

Null class is not robust so is a Gaussian ?

Inheritance diagram for gtsam::noiseModel::mEstimator::Null:

Public Member Functions
	Null (const ReweightScheme reweight=Block)

virtual double	weight (double) const

virtual void	print (const std::string &s) const

virtual bool	equals (const Base &, double) const

Public Member Functions inherited from gtsam::noiseModel::mEstimator::Base
	Base (const ReweightScheme reweight=Block)

virtual double	residual (double error) const

double	sqrtWeight (double error) const

Vector	weight (const Vector &error) const
	produce a weight vector according to an error vector and the implemented robust function

Vector	sqrtWeight (const Vector &error) const
	square root version of the weight function

void	reweight (Vector &error) const
	reweight block matrices and a vector according to their weight implementation

void	reweight (std::vector< Matrix > &A, Vector &error) const

void	reweight (Matrix &A, Vector &error) const

void	reweight (Matrix &A1, Matrix &A2, Vector &error) const

void	reweight (Matrix &A1, Matrix &A2, Matrix &A3, Vector &error) const

Static Public Member Functions
static shared_ptr	Create ()

Public Types
typedef boost::shared_ptr< Null >	shared_ptr

Public Types inherited from gtsam::noiseModel::mEstimator::Base
enum	ReweightScheme { Scalar, Block }

typedef boost::shared_ptr< Base >	shared_ptr

Additional Inherited Members
Protected Attributes inherited from gtsam::noiseModel::mEstimator::Base
ReweightScheme	reweight_
	the rows can be weighted independently according to the error or uniformly with the norm of the right hand side

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

Public Member Functions