Class PDF: Virtual Base class representing Probability Density Functions. More...
#include <pdf.h>
Public Member Functions | |
| virtual Pdf< T > * | Clone () const =0 |
| Pure virtual clone function. | |
| virtual MatrixWrapper::SymmetricMatrix | CovarianceGet () const |
| Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf. | |
| unsigned int | DimensionGet () const |
| Get the dimension of the argument. | |
| virtual void | DimensionSet (unsigned int dim) |
| Set the dimension of the argument. | |
| virtual T | ExpectedValueGet () const |
| Get the expected value E[x] of the pdf. | |
| Pdf (unsigned int dimension=0) | |
| Constructor. | |
| virtual Probability | ProbabilityGet (const T &input) const |
| Get the probability of a certain argument. | |
| virtual bool | SampleFrom (vector< Sample< T > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const |
| Draw multiple samples from the Pdf (overloaded) | |
| virtual bool | SampleFrom (Sample< T > &one_sample, int method=DEFAULT, void *args=NULL) const |
| Draw 1 sample from the Pdf: | |
| virtual | ~Pdf () |
| Destructor. | |
Private Attributes | |
| unsigned int | _dimension |
| Dimension of the argument x of P(x | ...). | |
Class PDF: Virtual Base class representing Probability Density Functions.
Constructor.
| dimension | int representing the number of rows of the state |
Pure virtual clone function.
| virtual MatrixWrapper::SymmetricMatrix BFL::Pdf< T >::CovarianceGet | ( | ) | const [virtual] |
| unsigned int BFL::Pdf< T >::DimensionGet | ( | ) | const |
Get the dimension of the argument.
| virtual void BFL::Pdf< T >::DimensionSet | ( | unsigned int | dim | ) | [virtual] |
Set the dimension of the argument.
| dim | the dimension |
| virtual T BFL::Pdf< T >::ExpectedValueGet | ( | ) | const [virtual] |
Get the expected value E[x] of the pdf.
Get low order statistic (Expected Value) of this AnalyticPdf
| virtual Probability BFL::Pdf< T >::ProbabilityGet | ( | const T & | input | ) | const [virtual] |
Get the probability of a certain argument.
| input | T argument of the Pdf |
| virtual bool BFL::Pdf< T >::SampleFrom | ( | vector< Sample< T > > & | list_samples, |
| const unsigned int | num_samples, | ||
| int | method = DEFAULT, |
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| void * | args = NULL |
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| ) | const [virtual] |
Draw multiple samples from the Pdf (overloaded)
| list_samples | list of samples that will contain result of sampling |
| num_samples | Number of Samples to be drawn (iid) |
| method | Sampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1 |
| args | Pointer to a struct representing extra sample arguments. "Sample Arguments" can be anything (the number of steps a gibbs-iterator should take, the interval width in MCMC, ... (or nothing), so it is hard to give a meaning to what exactly Sample Arguments should represent... |
| virtual bool BFL::Pdf< T >::SampleFrom | ( | Sample< T > & | one_sample, |
| int | method = DEFAULT, |
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| void * | args = NULL |
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| ) | const [virtual] |
Draw 1 sample from the Pdf:
There's no need to create a list for only 1 sample!
| one_sample | sample that will contain result of sampling |
| method | Sampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1 |
| args | Pointer to a struct representing extra sample arguments |
unsigned int BFL::Pdf< T >::_dimension [private] |