queso-0.51.1
BayesianJointPdf.h
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4 // QUESO - a library to support the Quantification of Uncertainty
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24 
25 #ifndef UQ_BAYESIAN_JOINT_PROB_DENSITY_H
26 #define UQ_BAYESIAN_JOINT_PROB_DENSITY_H
27 
28 #include <cmath>
29 
30 #include <boost/math/special_functions.hpp> // for Boost isnan. Note parentheses are important in function call.
31 
32 #include <queso/JointPdf.h>
33 #include <queso/Environment.h>
34 #include <queso/ScalarFunction.h>
35 #include <queso/BoxSubset.h>
36 
37 namespace QUESO {
38 
39 //*****************************************************
40 // Bayesian probability density class [PDF-02]
41 //*****************************************************
48 template<class V, class M>
49 class BayesianJointPdf : public BaseJointPdf<V,M> {
50 public:
52 
53 
57  BayesianJointPdf(const char* prefix,
58  const BaseJointPdf <V,M>& priorDensity,
59  const BaseScalarFunction<V,M>& likelihoodFunction,
60  double likelihoodExponent,
61  const VectorSet <V,M>& intersectionDomain);
64 
65 
67 
68 
72  double actualValue (const V& domainVector, const V* domainDirection, V* gradVector, M* hessianMatrix, V* hessianEffect) const;
73 
75 
79  double lnValue (const V& domainVector, const V* domainDirection, V* gradVector, M* hessianMatrix, V* hessianEffect) const;
80 
82 
83  double computeLogOfNormalizationFactor(unsigned int numSamples, bool updateFactorInternally) const;
84 
85 
87  void setNormalizationStyle (unsigned int value) const;
88 
90  double lastComputedLogPrior () const;
91 
93  double lastComputedLogLikelihood() const;
94 
96 
97 protected:
102 
106  mutable double m_lastComputedLogPrior;
108 
109  mutable V m_tmpVector1;
110  mutable V m_tmpVector2;
111  mutable M* m_tmpMatrix;
112 };
113 
114 } // End namespace QUESO
115 
116 #endif // UQ_BAYESIAN_JOINT_PROB_DENSITY_H
double actualValue(const V &domainVector, const V *domainDirection, V *gradVector, M *hessianMatrix, V *hessianEffect) const
Actual value of the PDF (scalar function).
double lastComputedLogLikelihood() const
Returns the logarithm of the last computed likelihood value. Access to protected attribute m_lastComp...
A templated class for handling sets.
Definition: VectorSet.h:49
~BayesianJointPdf()
Destructor.
double lnValue(const V &domainVector, const V *domainDirection, V *gradVector, M *hessianMatrix, V *hessianEffect) const
Computes the logarithm of the value of the function.
double computeLogOfNormalizationFactor(unsigned int numSamples, bool updateFactorInternally) const
TODO: Computes the logarithm of the normalization factor.
const BaseJointPdf< V, M > & m_priorDensity
void setNormalizationStyle(unsigned int value) const
Sets a value to be used in the normalization style of the prior density PDF (ie, protected attribute ...
A templated (base) class for handling scalar functions.
Definition: GslOptimizer.h:48
double lastComputedLogPrior() const
Returns the logarithm of the last computed Prior value. Access to protected attribute m_lastComputedL...
BayesianJointPdf(const char *prefix, const BaseJointPdf< V, M > &priorDensity, const BaseScalarFunction< V, M > &likelihoodFunction, double likelihoodExponent, const VectorSet< V, M > &intersectionDomain)
Default constructor.
const BaseScalarFunction< V, M > & m_likelihoodFunction
A templated (base) class for handling joint PDFs.
Definition: JointPdf.h:60
A class for handling Bayesian joint PDFs.

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