queso-0.56.1
BayesianJointPdf.h
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3 //
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 #include <queso/math_macros.h>
30 #include <queso/JointPdf.h>
31 #include <queso/Environment.h>
32 #include <queso/ScalarFunction.h>
33 #include <queso/BoxSubset.h>
34 
35 namespace QUESO {
36 
37 class GslVector;
38 class GslMatrix;
39 
46 template <class V = GslVector, class M = GslMatrix>
47 class BayesianJointPdf : public BaseJointPdf<V,M> {
48 public:
50 
51 
55  BayesianJointPdf(const char* prefix,
56  const BaseJointPdf <V,M>& priorDensity,
57  const BaseScalarFunction<V,M>& likelihoodFunction,
58  double likelihoodExponent,
59  const VectorSet <V,M>& intersectionDomain);
62 
63 
65 
66 
70  double actualValue (const V& domainVector, const V* domainDirection, V* gradVector, M* hessianMatrix, V* hessianEffect) const;
71 
73 
77  double lnValue (const V& domainVector, const V* domainDirection, V* gradVector, M* hessianMatrix, V* hessianEffect) const;
78 
80  virtual void distributionMean (V & meanVector) const { queso_not_implemented(); }
81 
83  virtual void distributionVariance (M & covMatrix) const { queso_not_implemented(); };
84 
86 
87  double computeLogOfNormalizationFactor(unsigned int numSamples, bool updateFactorInternally) const;
88 
90  void setNormalizationStyle (unsigned int value) const;
91 
93  double lastComputedLogPrior () const;
94 
96  double lastComputedLogLikelihood() const;
97 
99 
100 protected:
105 
109  mutable double m_lastComputedLogPrior;
111 
112  mutable V m_tmpVector1;
113  mutable V m_tmpVector2;
114  mutable M* m_tmpMatrix;
115 };
116 
117 } // End namespace QUESO
118 
119 #endif // UQ_BAYESIAN_JOINT_PROB_DENSITY_H
A templated (base) class for handling scalar functions.
double lastComputedLogLikelihood() const
Returns the logarithm of the last computed likelihood value. Access to protected attribute m_lastComp...
const BaseScalarFunction< V, M > & m_likelihoodFunction
double actualValue(const V &domainVector, const V *domainDirection, V *gradVector, M *hessianMatrix, V *hessianEffect) const
Actual value of the PDF (scalar function).
~BayesianJointPdf()
Destructor.
A templated (base) class for handling joint PDFs.
Definition: JointPdf.h:55
BayesianJointPdf(const char *prefix, const BaseJointPdf< V, M > &priorDensity, const BaseScalarFunction< V, M > &likelihoodFunction, double likelihoodExponent, const VectorSet< V, M > &intersectionDomain)
Default constructor.
#define queso_not_implemented()
Definition: asserts.h:56
double lnValue(const V &domainVector, const V *domainDirection, V *gradVector, M *hessianMatrix, V *hessianEffect) const
Computes the logarithm of the value of the function.
virtual void distributionVariance(M &covMatrix) const
Covariance matrix of the underlying random variable.
void setNormalizationStyle(unsigned int value) const
Sets a value to be used in the normalization style of the prior density PDF (ie, protected attribute ...
const BaseJointPdf< V, M > & m_priorDensity
virtual void distributionMean(V &meanVector) const
Mean value of the underlying random variable.
double computeLogOfNormalizationFactor(unsigned int numSamples, bool updateFactorInternally) const
TODO: Computes the logarithm of the normalization factor.
double lastComputedLogPrior() const
Returns the logarithm of the last computed Prior value. Access to protected attribute m_lastComputedL...

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