Class PDF: Virtual Base class representing Probability Density Functions.
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#include <pdf.h>
template<typename T>
class BFL::Pdf< T >
Class PDF: Virtual Base class representing Probability Density Functions.
Definition at line 76 of file pdf.h.
◆ Pdf()
Pdf |
( |
unsigned int |
dimension = 0 | ) |
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Constructor.
- Parameters
-
dimension | int representing the number of rows of the state |
Definition at line 173 of file pdf.h.
◆ CovarianceGet()
Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
Get first order statistic (Covariance) of this AnalyticPdf
- Returns
- The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)
- Todo:
- extend this more general to n-th order statistic
- Bug:
- Discrete pdfs should not be able to use this!
Reimplemented in Mixture< T >, and MCPdf< T >.
Definition at line 248 of file pdf.h.
◆ DimensionGet()
unsigned int DimensionGet |
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inline |
Get the dimension of the argument.
- Returns
- the dimension of the argument
Definition at line 192 of file pdf.h.
◆ DimensionSet()
void DimensionSet |
( |
unsigned int |
dim | ) |
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virtual |
Set the dimension of the argument.
- Parameters
-
Reimplemented in Gaussian.
Definition at line 198 of file pdf.h.
◆ ExpectedValueGet()
Get the expected value E[x] of the pdf.
Get low order statistic (Expected Value) of this AnalyticPdf
- Returns
- The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
- Note
- No set functions here! This can be useful for analytic functions, but not for sample based representations!
-
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?
Reimplemented in Mixture< T >, and MCPdf< T >.
Definition at line 238 of file pdf.h.
◆ ProbabilityGet()
◆ SampleFrom() [1/2]
bool SampleFrom |
( |
Sample< T > & |
one_sample, |
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const SampleMthd |
method = SampleMthd::DEFAULT , |
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void * |
args = NULL |
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) |
| const |
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virtual |
◆ SampleFrom() [2/2]
bool SampleFrom |
( |
vector< Sample< T > > & |
list_samples, |
|
|
const unsigned int |
num_samples, |
|
|
const SampleMthd |
method = SampleMthd::DEFAULT , |
|
|
void * |
args = NULL |
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) |
| const |
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virtual |
Draw multiple samples from the Pdf (overloaded)
- Parameters
-
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 an enum eg. SampleMthd::BOXMULLER |
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... |
- Todo:
- replace the C-call "void * args" by a more object-oriented structure: Perhaps something like virtual Sample * Sample (const int num_samples,class Sampler)
- Bug:
- Sometimes the compiler doesn't know which method to choose!
Reimplemented in Mixture< T >, MCPdf< T >, Gaussian, Uniform, DiscreteConditionalPdf, and DiscretePdf.
Definition at line 205 of file pdf.h.
The documentation for this class was generated from the following file: