bdm::migamma_ref Class Reference

Inverse-Gamma random walk around a fixed point. More...

#include <exp_family.h>

List of all members.

Public Member Functions

migamma_ref ()

Constructor.

void set_parameters (double k0, vec ref0, double l0)

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)

void set_parameters (int len, double k0)

Set value of k.

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.

Matematical operations

virtual vec samplecond (const vec &cond)

Returns a sample from the density conditioned on cond, $x \sim epdf(rv|cond)$ .

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 * e ()

void set_ep (shared_ptr< epdf > ep)

Connection to other objects

void set_rvc (const RV &rvc0)

void set_rv (const RV &rv0)

bool isnamed ()

Protected Attributes

double l

parameter l

vec refl

reference vector

shared_ptr< eigamma > iepdf

Internal epdf that arise by conditioning on rvc.

double k

Constant $k$ .

vec & _alpha

cache of iepdf.alpha

vec & _beta

cache of iepdf.beta

int dimc

dimension of the condition

RV rvc

random variable in condition

Detailed Description

Inverse-Gamma random walk around a fixed point.

Mean value, $\mu$ , of this density is given by a geometric combination of rvc and given fixed point, $p$ . $l$ is the coefficient of the geometric combimation

$\mu = \mu_{t-1} ^{l} p^{1-l}$

==== Check == vv = Standard deviation of the random walk is proportional to one $k$ -th the mean. This is achieved by setting $\alpha=k$ and $\beta=k/\mu$ .

The standard deviation of the walk is then: $\mu/\sqrt(k)$ .

Member Function Documentation

void bdm::migamma_ref::from_setting ( const Setting & set ) [virtual]

UI for migamma_ref

The migamma_ref is constructed from a structure with fields:

                        system = {
                                type = "migamma_ref";
                                ref = [1e-5; 1e-5; 1e-2 1e-3];            // reference vector
                                l = 0.999;                                // constant l
                                k = 0.1;                                  // constant k
                                
                                // == OPTIONAL ==
                                // description of y variables
                                y = {type="rv"; names=["y", "u"];};
                                // description of u variable
                                u = {type="rv"; names=[];}
                        };

Result if

Reimplemented from bdm::mpdf.

References bdm::UI::get(), and set_parameters().

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

Returns a sample from the density conditioned on cond, $x \sim epdf(rv|cond)$ .

Parameters:

cond is numeric value of rv

Reimplemented in bdm::mprod.

References bdm::mpdf::condition().

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

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

Returns.

Parameters:

	N	samples from the density conditioned on `cond`, $x \sim epdf(rv\|cond)$ .
	cond	is numeric value of `rv`

References bdm::mpdf::condition().

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

exp_family.h
exp_family.cpp


Public Member Functions
	migamma_ref ()
	Constructor.
void	set_parameters (double k0, vec ref0, double l0)
	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)
void	set_parameters (int len, double k0)
	Set value of `k`.
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.
Matematical operations
virtual vec	samplecond (const vec &cond)
	Returns a sample from the density conditioned on `cond`, $x \sim epdf(rv\|cond)$ .
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 *	e ()
void	set_ep (shared_ptr< epdf > ep)
Connection to other objects
void	set_rvc (const RV &rvc0)
void	set_rv (const RV &rv0)
bool	isnamed ()
Protected Attributes
double	l
	parameter l
vec	refl
	reference vector
shared_ptr< eigamma >	iepdf
	Internal epdf that arise by conditioning on `rvc`.
double	k
	Constant .
vec &	_alpha
	cache of iepdf.alpha
vec &	_beta
	cache of iepdf.beta
int	dimc
	dimension of the condition
RV	rvc
	random variable in condition