ROOT   Reference Guide
ROOT::Minuit2::FumiliErrorUpdator Class Reference

In the case of the Fumili algorithm the Error matrix (or the Hessian matrix containing the (approximate) second derivatives) is calculated using a linearization of the model function negleting second derivatives.

(In some sense the Name Updator is a little bit misleading as the Error matrix is not calculated by iteratively updating, like in Davidon's or other similar variable metric methods, but by recalculating each time).

MINUIT Tutorial on function minimization, section 5
DavidonErrorUpdator

Definition at line 47 of file FumiliErrorUpdator.h.

## Public Member Functions

FumiliErrorUpdator ()

~FumiliErrorUpdator ()

virtual MinimumError Update (const MinimumState &, const MinimumParameters &, const FunctionGradient &) const
Member function which is only present due to the design already in place of the software. More...

virtual MinimumError Update (const MinimumState &fMinimumState, const MinimumParameters &fMinimumParameters, const GradientCalculator &fGradientCalculator, double lambda) const
Member function that calculates the Error matrix (or the Hessian matrix containing the (approximate) second derivatives) using a linearization of the model function negleting second derivatives. More...

Public Member Functions inherited from ROOT::Minuit2::MinimumErrorUpdator
virtual ~MinimumErrorUpdator ()

virtual MinimumError Update (const MinimumState &, const MinimumParameters &, const FunctionGradient &) const =0

#include <Minuit2/FumiliErrorUpdator.h>

Inheritance diagram for ROOT::Minuit2::FumiliErrorUpdator:

## ◆ FumiliErrorUpdator()

 ROOT::Minuit2::FumiliErrorUpdator::FumiliErrorUpdator ( )
inline

Definition at line 50 of file FumiliErrorUpdator.h.

## ◆ ~FumiliErrorUpdator()

 ROOT::Minuit2::FumiliErrorUpdator::~FumiliErrorUpdator ( )
inline

Definition at line 52 of file FumiliErrorUpdator.h.

## ◆ Update() [1/2]

 MinimumError ROOT::Minuit2::FumiliErrorUpdator::Update ( const MinimumState & s0, const MinimumParameters & p1, const FunctionGradient & g1 ) const
virtual

Member function which is only present due to the design already in place of the software.

As all classes calculating the Error matrix are supposed inherit from the MinimumErrorUpdator they must inherit this method. In some methods calculating the aforementioned matrix some of these parameters are not needed and other parameters are necessary... Hopefully, a more elegant solution will be found in the future.

Implements ROOT::Minuit2::MinimumErrorUpdator.

Definition at line 32 of file FumiliErrorUpdator.cxx.

## ◆ Update() [2/2]

 MinimumError ROOT::Minuit2::FumiliErrorUpdator::Update ( const MinimumState & fMinimumState, const MinimumParameters & fMinimumParameters, const GradientCalculator & fGradientCalculator, double lambda ) const
virtual

Member function that calculates the Error matrix (or the Hessian matrix containing the (approximate) second derivatives) using a linearization of the model function negleting second derivatives.

Parameters
 fMinimumState used to calculate the change in the covariance matrix between the two iterations fMinimumParameters the parameters at the present iteration fGradientCalculator the Gradient calculator used to retrieved the Parameter transformation lambda the Marquard lambda factor

Definition at line 43 of file FumiliErrorUpdator.cxx.

Collaboration diagram for ROOT::Minuit2::FumiliErrorUpdator:

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