# bdm::migamma Class Reference

Inverse-Gamma random walk. More...

`#include <exp_family.h>`

List of all members.

## Public Member Functions
void | set_parameters (int len, double k0)
| Set value of `k`.
void | condition (const vec &val)
| Update `ep` so that it represents this mpdf conditioned on `rvc` = cond.
void | from_setting (const Setting &set)
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.
virtual void | validate ()
| This method TODO.
Constructors
| migamma ()
| migamma (const migamma &m)
Matematical operations
virtual vec | samplecond (const vec &cond)
| Returns a sample from the density conditioned on `cond`, .
virtual mat | samplecond_m (const vec &cond, int N)
| Returns.
virtual double | evallogcond (const vec &dt, const vec &cond)
| Shortcut for conditioning and evaluation of the internal epdf. In some cases, this operation can be implemented efficiently.
virtual vec | evallogcond_m (const mat &Dt, const vec &cond)
| Matrix version of evallogcond.
virtual vec | evallogcond_m (const Array< vec > &Dt, const vec &cond)
| Array<vec> version of evallogcond.
Access to attributes
RV | _rv ()
RV | _rvc ()
int | dimension ()
int | dimensionc ()
epdf & | _epdf ()
epdf * | _e ()
Connection to other objects
void | set_rvc (const RV &rvc0)
void | set_rv (const RV &rv0)
bool | isnamed ()
## Protected Attributes
eigamma | epdf
| Internal epdf that arise by conditioning on `rvc`.
double | k
| Constant .
vec & | _alpha
| cache of epdf.alpha
vec & | _beta
| cache of epdf.beta
int | dimc
| dimension of the condition
RV | rvc
| random variable in condition
epdf * | ep
| pointer to internal epdf

## Detailed Description

Inverse-Gamma random walk.

Mean value, , of this density is given by `rvc` . Standard deviation of the random walk is proportional to one -th the mean. This is achieved by setting and .

The standard deviation of the walk is then: .

## Member Function Documentation

void bdm::mpdf::from_setting | ( | const Setting & | set | ) | `[inline, virtual, inherited]`

Load from structure with elements:

     { rv = {class="RV", names=(...),}; // RV describing meaning of random variable
       rvc= {class="RV", names=(...),}; // RV describing meaning of random variable in condition
       // elements of offsprings
     }

Reimplemented from bdm::root.

Reimplemented in bdm::mepdf, bdm::mprod, bdm::mgnorm< sq_T >, bdm::mgamma, bdm::migamma_ref, and bdm::mlognorm.

virtual vec bdm::mpdf::samplecond | ( | const vec & | cond | ) | `[inline, virtual, inherited]`

Returns a sample from the density conditioned on `cond`, .

Parameters:

  | cond | is numeric value of `rv`

Reimplemented in bdm::mprod.

References bdm::mpdf::condition(), bdm::mpdf::ep, and bdm::epdf::sample().

Referenced by bdm::MPF< BM_T >::bayes(), bdm::PF::bayes(), and bdm::ArxDS::step().

virtual mat bdm::mpdf::samplecond_m | ( | const vec & | cond,
|  | int | N |
| ) |  |  | `[inline, virtual, inherited]`

Returns.

Parameters:

  | N | samples from the density conditioned on `cond`, .
  | cond | is numeric value of `rv`

References bdm::mpdf::condition(), bdm::epdf::dimension(), bdm::mpdf::ep, and bdm::epdf::sample().

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

- exp_family.h