# bdm::egiw Class Reference

Gauss-inverse-Wishart density stored in LD form. More...

`#include <libEF.h>`

List of all members.

## Public Member Functions
vec | sample () const
| Returns a sample, from density .
vec | mean () const
| return expected value
vec | variance () const
| return expected variance (not covariance!)
vec | est_theta () const
| LS estimate of .
ldmat | est_theta_cov () const
| Covariance of the LS estimate.
void | mean_mat (mat &M, mat &R) const
double | evallog_nn (const vec &val) const
| In this instance, val= [theta, r]. For multivariate instances, it is stored columnwise val = [theta_1 theta_2 ... r_1 r_2 ].
double | lognc () const
| logarithm of the normalizing constant,
void | pow (double p)
| Power of the density, used e.g. to flatten the density.
virtual void | dupdate (mat &v)
| TODO decide if it is really needed.
virtual double | evallog (const vec &val) const
| Evaluate normalized log-probability.
virtual vec | evallog (const mat &Val) const
| Evaluate normalized log-probability for many samples.
virtual string | ToString ()
| This method returns a basic info about the current instance.
virtual void | from_setting (const Setting &root)
| This method arrange instance properties according the data stored in the Setting structure.
virtual void | to_setting (Setting &root) const
| This method save all the instance properties into the Setting structure.
Constructors
| egiw ()
| egiw (int dimx0, ldmat V0, double nu0=-1.0)
void | set_parameters (int dimx0, ldmat V0, double nu0=-1.0)
Access attributes
ldmat & | _V ()
const ldmat & | _V () const
double & | _nu ()
const double & | _nu () const
Constructors
Construction of each epdf should support two types of constructors: empty constructor, copy constructor, The following constructors should be supported for convenience: constructor followed by calling `set_parameters()` constructor accepting random variables calling `set_rv()` All internal data structures are constructed as empty. Their values (including sizes) will be set by method `set_parameters()`. This way references can be initialized in constructors.
void | set_parameters (int dim0)
Matematical Operations
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.
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
Description of the random quantity via attribute `rv` is optional. For operations such as sampling `rv` does not need to be set. However, for `marginalization` and `conditioning` `rv` has to be set. NB:
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
ldmat | V
| Extended information matrix of sufficient statistics.
double | nu
| Number of data records (degrees of freedom) of sufficient statistics.
int | dimx
| Dimension of the output.
int | nPsi
| Dimension of the regressor.
int | dim
| dimension of the random variable
RV | rv
| Description of the random variable.

## Detailed Description

Gauss-inverse-Wishart density stored in LD form.

For -variate densities, given rv.count() should be V.rows().

The documentation for this class was generated from the following files:

- libEF.h
- libEF.cpp