Gaussian density with positive definite (decomposed) covariance matrix. More...
Gaussian density with positive definite (decomposed) covariance matrix.
More?...
#include <exp_family.h>
Public Member Functions | |
virtual double | evallog (const vec &val) const |
Evaluate normalized log-probability. | |
virtual vec | evallog_m (const mat &Val) const |
Evaluate normalized log-probability for many samples. | |
virtual vec | evallog_m (const Array< vec > &Val) const |
Evaluate normalized log-probability for many samples. | |
virtual void | pow (double p) |
Power of the density, used e.g. to flatten the density. | |
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. | |
Constructors | |
enorm () | |
enorm (const vec &mu, const sq_T &R) | |
void | set_parameters (const vec &mu, const sq_T &R) |
void | from_setting (const Setting &root) |
Load from structure with elements:. | |
void | validate () |
This method TODO. | |
Mathematical operations | |
void | dupdate (mat &v, double nu=1.0) |
dupdate in exponential form (not really handy) | |
vec | sample () const |
Returns a sample, from density . | |
double | evallog_nn (const vec &val) const |
Evaluate normalized log-probability. | |
double | lognc () const |
logarithm of the normalizing constant, | |
vec | mean () const |
return expected value | |
vec | variance () const |
return expected variance (not covariance!) | |
shared_ptr< mpdf > | condition (const RV &rvn) const |
Return conditional density on the given RV, the remaining rvs will be in conditioning. | |
void | condition (const RV &rvn, mpdf &target) const |
shared_ptr< epdf > | marginal (const RV &rvn) const |
Return marginal density on the given RV, the remainig rvs are intergrated out. | |
void | marginal (const RV &rvn, enorm< sq_T > &target) const |
Access to attributes | |
vec & | _mu () |
const vec & | _mu () const |
void | set_mu (const vec mu0) |
sq_T & | _R () |
const sq_T & | _R () const |
Constructors | |
Construction of each epdf should support two types of constructors:
The following constructors should be supported for convenience:
All internal data structures are constructed as empty. Their values (including sizes) will be set by method | |
void | set_parameters (int dim0) |
Matematical Operations | |
virtual mat | sample_m (int N) const |
Returns N samples, from density . | |
virtual void | qbounds (vec &lb, vec &ub, double percentage=0.95) const |
Lower and upper bounds of percentage % quantile, returns mean-2*sigma as default. | |
Connection to other classes | |
void | set_rv (const RV &rv0) |
Name its rv. | |
bool | isnamed () const |
True if rv is assigned. | |
const RV & | _rv () const |
Return name (fails when isnamed is false). | |
Access to attributes | |
int | dimension () const |
Size of the random variable. | |
Protected Attributes | |
vec | mu |
mean value | |
sq_T | R |
Covariance matrix in decomposed form. | |
int | dim |
dimension of the random variable | |
RV | rv |
Description of the random variable. |
void bdm::enorm< sq_T >::from_setting | ( | const Setting & | set | ) | [inline, virtual] |
Load from structure with elements:.
{ rv = {class="RV", names=(...),}; // RV describing meaning of random variable // elements of offsprings }
Reimplemented from bdm::epdf.
References bdm::UI::get(), bdm::enorm< sq_T >::mu, bdm::enorm< sq_T >::R, and bdm::enorm< sq_T >::validate().