Concrete profileable likelihood built from a model and joint distributions. More...

#include <memory>
#include <vector>
#include "IProfileableLikelihood.h"
#include "JointDistribution.h"
#include "Math.h"

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Classes
struct	LikelihoodContext
	Shared immutable-like data required to evaluate a likelihood. More...

class	BaseLikelihood
	Default implementation of a profileable negative log-likelihood. More...

Typedefs
using	ModelFn = std::function< std::vector< double >(const std::vector< double > &p, const std::vector< double > &eta)>
	Model function signature used by BaseLikelihood.

Detailed Description

Concrete profileable likelihood built from a model and joint distributions.

The likelihood combines:

a user-provided model function mapping fitted and nuisance parameters to observable predictions,
a joint distribution for the experimental observables,
a joint distribution for the nuisance parameters.

The optimization vector is ordered as $\theta = (p, \eta)$ , where $p$ denotes fitted parameters and $\eta$ denotes nuisance parameters.

See also: IProfileableLikelihood; JointDistribution

Definition in file BaseLikelihood.h.

Typedef Documentation

◆ ModelFn

using ModelFn = std::function<std::vector<double>(const std::vector<double>& p, const std::vector<double>& eta)>

Model function signature used by BaseLikelihood.

The function receives the fitted-parameter block $p$ and the nuisance block $\eta$ , and returns the corresponding model prediction in observable space.

Definition at line 35 of file BaseLikelihood.h.

Classes

Typedefs

Detailed Description

Typedef Documentation

◆ ModelFn