bdm::enorm< sq_T > Class Template Reference
Gaussian density with positive definite (decomposed) covariance matrix. More...
Detailed Description
template<class sq_T>
class bdm::enorm< sq_T >
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) |
| 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. | |
Member Function Documentation
template<class sq_T >
| void bdm::enorm< sq_T >::from_setting | ( | const Setting & | root | ) | [inline, virtual] |
Create Normal density
![\[ f(rv) = N(\mu, R) \]](form_164.png)
from structure
class = 'enorm<ldmat>', (OR) 'enorm<chmat>', (OR) 'enorm<fsqmat>'; mu = []; // mean value R = []; // variance, square matrix of appropriate dimension
Reimplemented from bdm::epdf.
References bdm::UI::get(), bdm::enorm< sq_T >::mu, bdm::enorm< sq_T >::R, and bdm::enorm< sq_T >::validate().
The documentation for this class was generated from the following file:
