ComPWA
Common Partial-Wave-Analysis Framework
Public Member Functions | Private Attributes | List of all members
ComPWA::Estimator::MinLogLH Class Reference

Negative Log Likelihood-Estimator. More...

#include <MinLogLH.hpp>

Public Member Functions

 MinLogLH (ComPWA::Intensity &intensity, const Data::DataSet &datasample, const Data::DataSet &phspdatasample)
 
double evaluate () noexcept final
 Value of log likelihood function. More...
 
void updateParametersFrom (const std::vector< double > &params) final
 It is important to input the vector in the same length and order as defined in the getParameters() method. More...
 
std::vector< ComPWA::Parameter > getParameters () const final
 
- Public Member Functions inherited from ComPWA::Function< double >
virtual ~Function ()=default
 
virtual double evaluate (const InputTypes &... args) noexcept=0
 

Private Attributes

ComPWA::Intensity & Intensity
 
const Data::DataSet & DataSample
 
const Data::DataSet & PhspDataSample
 

Detailed Description

Negative Log Likelihood-Estimator.

This class calculates the negative log likelihood -log(LH) using an Intensity and data samples. Data data samples are retrieved from the DataStorage.

log likelihood
The negative log LH is given by:

\[ -log \mathcal{L} = N_{\mathrm{obs}} * \log(\lambda) - \sum_i^{N_{\mathrm{obs}}} \log(I(x_i)) \]

with the Intensity $I(x_i)$ for a given event $x_i$ and the phase integral $ \lambda = \frac{V}{\sum w_i}\sum_i^{N_{\mathrm{phsp}}} I(x_i)\cdot \epsilon_i \cdot w_i $ $ \epsilon $ and $ w $ are the efficiency and weight for each event $ V $ is the phase space volume (in which the phase space events lie)

The sum over all weights is necessary to normalize the weights to one. Otherwise the error estimate would be incorrect. The Intensity does not have to be normalized. This is done automatically by the phase space integral.

Efficiency correction
It is assumed that the data already includes the efficiency.

Definition at line 50 of file MinLogLH.hpp.

+ Inheritance diagram for ComPWA::Estimator::MinLogLH:
+ Collaboration diagram for ComPWA::Estimator::MinLogLH:

Constructor & Destructor Documentation

◆ MinLogLH()

ComPWA::Estimator::MinLogLH::MinLogLH ( ComPWA::Intensity &  intensity,
const Data::DataSet &  datasample,
const Data::DataSet &  phspdatasample 
)

Definition at line 17 of file MinLogLH.cpp.

Member Function Documentation

◆ evaluate()

double ComPWA::Estimator::MinLogLH::evaluate ( )
finalnoexcept

Value of log likelihood function.

Definition at line 27 of file MinLogLH.cpp.

◆ getParameters()

std::vector< ComPWA::Parameter > ComPWA::Estimator::MinLogLH::getParameters ( ) const
finalvirtual

Implements ComPWA::Function< double >.

Definition at line 59 of file MinLogLH.cpp.

◆ updateParametersFrom()

void ComPWA::Estimator::MinLogLH::updateParametersFrom ( const std::vector< double > &  )
finalvirtual

It is important to input the vector in the same length and order as defined in the getParameters() method.

So in other words, call getParameters() first, then use this ordering and to input new values in this method.

Implements ComPWA::Function< double >.

Definition at line 55 of file MinLogLH.cpp.

Member Data Documentation

◆ DataSample

const Data::DataSet& ComPWA::Estimator::MinLogLH::DataSample
private

Definition at line 66 of file MinLogLH.hpp.

◆ Intensity

ComPWA::Intensity& ComPWA::Estimator::MinLogLH::Intensity
private

Definition at line 64 of file MinLogLH.hpp.

◆ PhspDataSample

const Data::DataSet& ComPWA::Estimator::MinLogLH::PhspDataSample
private

Definition at line 67 of file MinLogLH.hpp.

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