#include <libEF.h>


Public Member Functions | |
| eigamma (const RV &rv) | |
| Default constructor.  | |
| void | set_parameters (const vec &a, const vec &b) | 
| Sets parameters.  | |
| vec | sample () const | 
Returns a sample,   from density  .  | |
| double | evallog (const vec &val) const | 
| TODO: is it used anywhere?  | |
| double | lognc () const | 
logarithm of the normalizing constant,    | |
| void | _param (vec *&a, vec *&b) | 
| Returns poiter to alpha and beta. Potentially dangerous: use with care!  | |
| vec | mean () const | 
| return expected value  | |
| vec | variance () const | 
| return expected variance (not covariance!)  | |
| virtual void | dupdate (mat &v) | 
| TODO decide if it is really needed.  | |
| virtual double | evallog_nn (const vec &val) const | 
| Evaluate normalized log-probability.  | |
| virtual vec | evallog (const mat &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 mat | sample_m (int N) const | 
Returns N samples from density  .  | |
| virtual vec | evallog_m (const mat &Val) const | 
Compute log-probability of multiple values argument val.  | |
| virtual mpdf * | condition (const RV &rv) const | 
| Return conditional density on the given RV, the remaining rvs will be in conditioning.  | |
| virtual epdf * | marginal (const RV &rv) const | 
| Return marginal density on the given RV, the remainig rvs are intergrated out.  | |
| const RV & | _rv () const | 
| access function, possibly dangerous!  | |
| void | _renewrv (const RV &in_rv) | 
| modifier function - useful when copying epdfs  | |
Protected Attributes | |
| vec * | alpha | 
Vector  .  | |
| vec * | beta | 
Vector   (in fact it is 1/beta as used in definition of iG).  | |
| egamma | eg | 
| internal egamma  | |
| RV | rv | 
| Identified of the random variable.  | |
Multivariate inverse-Gamma density as product of independent univariate densities.
Inverse Gamma can be converted to Gamma using \[ x iG(a,b) => 1/x G(a,1/b) \] This relation is used in sampling.
 1.5.6