Bayesian Filtering Library
Generated from SVN r
|
34 mutable bool _Sigma_changed;
36 mutable double _sqrt_pow;
37 mutable ColumnVector _diff;
38 mutable ColumnVector _tempColumn;
40 mutable ColumnVector _samples;
41 mutable ColumnVector _sampleValue;
42 mutable Matrix _Low_triangle;
69 const unsigned int num_samples,
70 const SampleMthd method=SampleMthd::DEFAULT,
71 void * args=NULL)
const;
void CovarianceSet(const MatrixWrapper::SymmetricMatrix &cov)
Set the Covariance Matrix.
Class representing Gaussian (or normal density)
friend std::ostream & operator<<(std::ostream &os, const Gaussian &g)
output stream for Gaussian
virtual void DimensionSet(unsigned int dim)
Set the dimension of the argument.
Gaussian(const MatrixWrapper::ColumnVector &Mu, const MatrixWrapper::SymmetricMatrix &Sigma)
Constructor.
Wrapper class for ColumnVectors (Boost implementation)
bool SampleFrom(vector< Sample< MatrixWrapper::ColumnVector > > &list_samples, const unsigned int num_samples, const SampleMthd method=SampleMthd::DEFAULT, void *args=NULL) const
Draw multiple samples from the Pdf (overloaded)
virtual ~Gaussian()
Default Copy Constructor will do.
void ExpectedValueSet(const MatrixWrapper::ColumnVector &mu)
Set the Expected Value.
virtual Gaussian * Clone() const
Clone function.
Class representing a probability (a double between 0 and 1)
virtual Probability ProbabilityGet(const MatrixWrapper::ColumnVector &input) const
Get the probability of a certain argument.
Class PDF: Virtual Base class representing Probability Density Functions.