Bayesian Filtering Library
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20 #ifndef __CONDITIONAL_GAUSSIAN__
21 #define __CONDITIONAL_GAUSSIAN__
23 #include "conditionalpdf.h"
63 const SampleMthd method=SampleMthd::DEFAULT,
void * args=NULL)
const;
67 mutable ColumnVector _diff;
68 mutable ColumnVector _Mu;
69 mutable Matrix _Low_triangle;
70 mutable ColumnVector _samples;
71 mutable ColumnVector _SampleValue;
77 #endif // __CONDITIONAL_GAUSSIAN__
Abstract Class representing conditional Pdfs P(x | ...)
Abstract Class representing all Conditional gaussians.
Wrapper class for ColumnVectors (Boost implementation)
ConditionalGaussian(int dim=0, int num_conditional_arguments=0)
Constructor.
virtual Probability ProbabilityGet(const MatrixWrapper::ColumnVector &input) const
Get the probability of a certain argument.
virtual bool SampleFrom(Sample< MatrixWrapper::ColumnVector > &sample, const SampleMthd method=SampleMthd::DEFAULT, void *args=NULL) const
Draw 1 sample from the Pdf:
Class representing a probability (a double between 0 and 1)
virtual ~ConditionalGaussian()
Destructor.
virtual ConditionalGaussian * Clone() const
Clone function.