#include <libEF.h>


Public Member Functions | |
| mgamma_fix (const RV &rv, const RV &rvc) | |
| Constructor. | |
| void | set_parameters (double k0, vec ref0, double l0) |
Set value of k. | |
| void | condition (const vec &val) |
Update ep so that it represents this mpdf conditioned on rvc = cond. | |
| void | set_parameters (double k) |
Set value of k. | |
| virtual vec | samplecond (const vec &cond, double &ll) |
| Returns the required moment of the epdf. | |
| virtual mat | samplecond_m (const vec &cond, vec &ll, 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. | |
| RV | _rvc () const |
| access function | |
| RV | _rv () const |
| access function | |
| epdf & | _epdf () |
| access function | |
Protected Attributes | |
| double | l |
| parameter l | |
| vec | refl |
| reference vector | |
| egamma | epdf |
Internal epdf that arise by conditioning on rvc. | |
| double | k |
Constant . | |
| vec * | _beta |
| cache of epdf.beta | |
| RV | rv |
| modeled random variable | |
| RV | rvc |
| random variable in condition | |
| epdf * | ep |
| pointer to internal epdf | |
Mean value,
, of this density is given by a geometric combination of rvc and given fixed point,
.
is the coefficient of the geometric combimation
Standard deviation of the random walk is proportional to one
-th the mean. This is achieved by setting
and
.
The standard deviation of the walk is then:
.
| virtual vec mpdf::samplecond | ( | const vec & | cond, | |
| double & | ll | |||
| ) | [inline, virtual, inherited] |
Returns the required moment of the epdf.
Returns a sample from the density conditioned on cond,
.
| cond | is numeric value of rv | |
| ll | is a return value of log-likelihood of the sample. |
Reimplemented in mprod.
References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample().
Referenced by MPF< BM_T >::bayes(), and PF::bayes().
| virtual mat mpdf::samplecond_m | ( | const vec & | cond, | |
| vec & | ll, | |||
| 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 mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
1.5.6