#include <exp_family.h>
Public Member Functions | |
mgamma_fix () | |
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, const vec &beta0) |
Set value of k . | |
void | from_setting (const Setting &set) |
virtual string | to_string () |
This method returns a basic info about the current instance. | |
virtual void | to_setting (Setting &set) const |
This method save all the instance properties into the Setting structure. | |
virtual void | validate () |
This method TODO. | |
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. | |
virtual vec | evallogcond_m (const Array< vec > &Dt, const vec &cond) |
Array<vec> version of evallogcond. | |
Access to attributes | |
RV | _rv () |
RV | _rvc () |
int | dimension () |
int | dimensionc () |
epdf * | e () |
void | set_ep (shared_ptr< epdf > ep) |
Connection to other objects | |
void | set_rvc (const RV &rvc0) |
void | set_rv (const RV &rv0) |
bool | isnamed () |
Protected Attributes | |
double | l |
parameter l | |
vec | refl |
reference vector | |
shared_ptr< egamma > | iepdf |
Internal epdf that arise by conditioning on rvc . | |
double | k |
Constant . | |
vec & | _beta |
cache of iepdf.beta | |
int | dimc |
dimension of the condition | |
RV | rvc |
random variable in condition |
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: .
void bdm::mgamma::from_setting | ( | const Setting & | set | ) | [inline, virtual, inherited] |
Load from structure with elements:
{ alpha = [...]; // vector of alpha k = 1.1; // multiplicative constant k rv = {class="RV",...} // description of RV rvc = {class="RV",...} // description of RV in condition }
Reimplemented from bdm::mpdf.
References bdm::UI::get(), bdm::mgamma::k, and bdm::mgamma::set_parameters().
vec bdm::mpdf::samplecond | ( | const vec & | cond | ) | [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().
Referenced by bdm::MPF< BM_T >::bayes(), bdm::PF::bayes(), and bdm::ArxDS::step().
mat bdm::mpdf::samplecond_m | ( | const vec & | cond, | |
int | N | |||
) | [virtual, inherited] |
Returns.
N | samples from the density conditioned on cond , . | |
cond | is numeric value of rv |
References bdm::mpdf::condition().