bdm::eigamma Class Reference
Inverse-Gamma posterior density. More...
#include <exp_family.h>
Public Member Functions | |
| double | evallog (const vec &val) const |
| Evaluate normalized log-probability. | |
| double | lognc () const |
logarithm of the normalizing constant,  | |
| vec & | _alpha () |
| Returns pointer to internal alpha. Potentially dengerous: use with care! | |
| vec & | _beta () |
| Returns pointer to internal beta. Potentially dengerous: use with care! | |
| void | from_setting (const Setting &set) |
| void | validate () |
| This method TODO. | |
| virtual double | evallog_nn (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. | |
| vec | sample () const |
Returns a sample,  from density  . | |
| vec | mean () const |
| Returns poiter to alpha and beta. Potentially dangerous: use with care! | |
| vec | variance () const |
| return expected variance (not covariance!) | |
Constructors | |
| void | set_parameters (const vec &a, const vec &b) |
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 shared_ptr< mpdf > | condition (const RV &rv) const |
| Return conditional density on the given RV, the remaining rvs will be in conditioning. | |
| virtual shared_ptr< epdf > | marginal (const RV &rv) const |
| Return marginal density on the given RV, the remainig rvs are intergrated out. | |
| 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 | alpha |
Vector  . | |
| vec | beta |
Vector  . | |
| int | dim |
| dimension of the random variable | |
| RV | rv |
| Description of the random variable. | |
Detailed Description
Inverse-Gamma posterior density.
Multivariate inverse-Gamma density as product of independent univariate densities.
![\[ f(x|\alpha,\beta) = \prod f(x_i|\alpha_i,\beta_i) \]](form_71.png)
Vector has different meaning (in fact it is 1/beta as used in definition of iG)
Inverse Gamma can be converted to Gamma using
![\[ x\sim iG(a,b) => 1/x\sim G(a,1/b) \]](form_73.png)
This relation is used in sampling.
Member Function Documentation
| void bdm::egamma::from_setting | ( | const Setting & | set | ) | [inline, virtual, inherited] |
Load from structure with elements:
{ alpha = [...]; // vector of alpha
beta = [...]; // vector of beta
rv = {class="RV",...} // description
}
Reimplemented from bdm::epdf.
References bdm::egamma::alpha, bdm::UI::get(), and bdm::egamma::validate().
The documentation for this class was generated from the following file:
