#include <libEF.h>
The internal epdf of this class is of the type of a Gaussian (enorm). However, each conditioning is trying to assure the best possible approximation by taking into account the zeta function. See [] for reference.
Perhaps a moment-matching technique?
Public Member Functions | |
void | set_parameters (const mat &A0, const vec &mu0, const ldmat &R0, const ldmat &Lambda0) |
void | condition (const vec &cond) |
vec & | _mu_const () |
access function | |
mat & | _A () |
access function | |
mat | _R () |
access function | |
Constructors | |
void | set_parameters (const mat &A, const vec &mu0, const ldmat &R) |
Set A and R . | |
Matematical operations | |
virtual vec | samplecond (const vec &cond) |
Returns a sample from the density conditioned on cond , . | |
virtual mat | samplecond_m (const vec &cond, int N) |
Returns. | |
virtual double | evallogcond (const vec &dt, const vec &cond) |
Shortcut for conditioning and evaluation of the internal epdf. In some cases, this operation can be implemented efficiently. | |
virtual vec | evallogcond_m (const mat &Dt, const vec &cond) |
Matrix version of evallogcond. | |
Access to attributes | |
RV | _rv () |
RV | _rvc () |
int | dimension () |
int | dimensionc () |
epdf & | _epdf () |
epdf * | _e () |
Connection to other objects | |
void | set_rvc (const RV &rvc0) |
void | set_rv (const RV &rv0) |
bool | isnamed () |
Protected Attributes | |
ldmat | Lambda |
ldmat & | _R |
ldmat | Re |
enorm< ldmat > | epdf |
Internal epdf that arise by conditioning on rvc . | |
mat | A |
vec | mu_const |
vec & | _mu |
int | dimc |
dimension of the condition | |
RV | rvc |
random variable in condition | |
epdf * | ep |
pointer to internal epdf | |
Friends | |
std::ostream & | operator<< (std::ostream &os, mlnorm< sq_M > &ml) |
void bdm::mlstudent::condition | ( | const vec & | cond | ) | [inline, virtual] |
Set value of rvc
. Result of this operation is stored in epdf
use function _ep
to access it.
Reimplemented from bdm::mlnorm< ldmat >.
References bdm::mlnorm< ldmat >::_R(), ldmat::invqform(), and ldmat::rows().
virtual vec bdm::mpdf::samplecond | ( | const vec & | cond | ) | [inline, virtual, inherited] |
Returns a sample from the density conditioned on cond
, .
cond | is numeric value of rv |
Reimplemented in bdm::mprod.
References bdm::mpdf::condition(), bdm::mpdf::ep, and bdm::epdf::sample().
Referenced by bdm::MPF< BM_T >::bayes(), bdm::PF::bayes(), and bdm::ArxDS::step().
virtual mat bdm::mpdf::samplecond_m | ( | const vec & | cond, | |
int | N | |||
) | [inline, virtual, inherited] |
Returns.
N | samples from the density conditioned on cond , . | |
cond | is numeric value of rv | |
ll | is a return value of log-likelihood of the sample. |
References bdm::mpdf::condition(), bdm::epdf::dimension(), bdm::mpdf::ep, and bdm::epdf::sample().