A helper class for the BCSummaryTool. More...
#include <BCSummaryPriorModel.h>
Inherits BCModel.
Public Member Functions | |
| BCSummaryPriorModel () | |
| BCSummaryPriorModel (const char *name) | |
| ~BCSummaryPriorModel () | |
| void | SetModel (BCModel *model) |
| double | LogAPrioriProbability (const std::vector< double > ¶meters) |
| double | LogLikelihood (const std::vector< double > ¶meters) |
Private Attributes | |
| BCModel * | fTestModel |
Detailed Description
A helper class for the BCSummaryTool.
Copyright (C) 2008-2012, Daniel Kollar and Kevin Kroeninger. All rights reserved.
For the licensing terms see doc/COPYING.
A helper class for the BCSummaryTool.
- Version:
- 1.0.0
- Date:
- 15.02.2010
Definition at line 28 of file BCSummaryPriorModel.h.
Constructor & Destructor Documentation
| BCSummaryPriorModel::BCSummaryPriorModel | ( | ) |
The default constructor.
Definition at line 18 of file BCSummaryPriorModel.cxx.
: BCModel() , fTestModel(0) { }
| BCSummaryPriorModel::BCSummaryPriorModel | ( | const char * | name | ) |
A constructor.
- Parameters:
-
name The name of the model.
Definition at line 25 of file BCSummaryPriorModel.cxx.
: BCModel(name) , fTestModel(0) { }
| BCSummaryPriorModel::~BCSummaryPriorModel | ( | ) |
Member Function Documentation
| double BCSummaryPriorModel::LogAPrioriProbability | ( | const std::vector< double > & | parameters | ) | [virtual] |
Calculates and returns the log of the prior probability at a given point in parameter space.
- Parameters:
-
parameters A vector of coordinates in the parameter space.
- Returns:
- The prior probability.
Reimplemented from BCModel.
Definition at line 80 of file BCSummaryPriorModel.cxx.
{
return 0;
}
| double BCSummaryPriorModel::LogLikelihood | ( | const std::vector< double > & | parameters | ) | [virtual] |
Calculates and returns the log of the Likelihood at a given point in parameter space.
- Parameters:
-
parameters A vector of coordinates in the parameter space.
- Returns:
- The log likelihood.
Implements BCModel.
Definition at line 74 of file BCSummaryPriorModel.cxx.
{
return fTestModel->LogAPrioriProbability(parameters);
}
| void BCSummaryPriorModel::SetModel | ( | BCModel * | model | ) |
Set a pointer to the model under study.
- Parameters:
-
model The model under study.
Definition at line 36 of file BCSummaryPriorModel.cxx.
{
fTestModel = model;
// copy parameters
int npar = fTestModel->GetNParameters();
for (int i = 0; i < npar; ++i) {
BCParameter * par = fTestModel->GetParameter(i);
AddParameter(par);
}
// set default histogram binning to the one of the original model
for (int i = 0; i < npar; ++i) {
// this construct has to go here, because otherwise there is a
// warning from BCEngineMCMC:: MCMCGetH1Marginalized
if (fTestModel->GetBestFitParameters().size() > 0){
BCH1D* hist = fTestModel->GetMarginalized( fTestModel->GetParameter(i) );
if (hist) {
int nbins = hist->GetHistogram()->GetNbinsX();
SetNbins( (fTestModel->GetParameter(i)->GetName()).c_str(), nbins);
}
}
}
// set default MCMC setup to the one of the original model
MCMCSetNChains( fTestModel->MCMCGetNChains() );
MCMCSetNLag( fTestModel->MCMCGetNLag() );
MCMCSetNIterationsMax( fTestModel->MCMCGetNIterationsMax() );
MCMCSetNIterationsRun( fTestModel->MCMCGetNIterationsRun() );
MCMCSetNIterationsPreRunMin( fTestModel->MCMCGetNIterationsPreRunMin() );
MCMCSetNIterationsUpdate( fTestModel->MCMCGetNIterationsUpdate() );
MCMCSetNIterationsUpdateMax( fTestModel->MCMCGetNIterationsUpdateMax() );
MCMCSetRValueCriterion( fTestModel->MCMCGetRValueCriterion() );
MCMCSetRValueParametersCriterion( fTestModel->MCMCGetRValueParametersCriterion() );
}
Member Data Documentation
BCModel* BCSummaryPriorModel::fTestModel [private] |
A pointer to the model under study.
Definition at line 70 of file BCSummaryPriorModel.h.
The documentation for this class was generated from the following files:
