mgamma_fix Class Reference

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

#include <libEF.h>

Inheritance diagram for mgamma_fix:

Collaboration diagram for mgamma_fix:

List of all members.

Public Member Functions

mgamma_fix (const RV &rv, const RV &rvc)

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 set_parameters (double k)

Set value of k.

virtual vec samplecond (const vec &cond, double &ll)

Returns the required moment of the epdf.

virtual mat samplecond (const vec &cond, vec &ll, int N)

Returns.

virtual double evalcond (const vec &dt, const vec &cond)

Shortcut for conditioning and evaluation of the internal epdf. In some cases, this operation can be implemented efficiently.

RV _rvc ()

access function

RV _rv ()

access function

epdf & _epdf ()

access function

Protected Attributes

double l

parameter l

vec refl

reference vector

egamma epdf

Internal epdf that arise by conditioning on rvc.

double k

Constant $k$ .

vec * _beta

cache of epdf.beta

RV rv

modeled random variable

RV rvc

random variable in condition

epdf * ep

pointer to internal epdf

Detailed Description

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

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

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

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

Returns the required moment of the epdf.

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

Parameters:

	cond	is numeric value of `rv`
	ll	is a return value of log-likelihood of the sample.

Reimplemented in mprod, and mlnorm< sq_T >.

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

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

virtual mat mpdf::samplecond	(	const vec &	cond,
		vec &	ll,
		int	N
	)			`[inline, virtual, inherited]`

Returns.

Parameters:

	N	samples from the density conditioned on `cond`, $x \sim epdf(rv\|cond)$ .
	cond	is numeric value of `rv`
	ll	is a return value of log-likelihood of the sample.

Reimplemented in mprod, and mlnorm< sq_T >.

References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().

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

work/git/mixpp/bdm/stat/libEF.h


Public Member Functions
	mgamma_fix (const RV &rv, const RV &rvc)
	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	set_parameters (double k)
	Set value of `k`.
virtual vec	samplecond (const vec &cond, double &ll)
	Returns the required moment of the epdf.
virtual mat	samplecond (const vec &cond, vec &ll, int N)
	Returns.
virtual double	evalcond (const vec &dt, const vec &cond)
	Shortcut for conditioning and evaluation of the internal epdf. In some cases, this operation can be implemented efficiently.
RV	_rvc ()
	access function
RV	_rv ()
	access function
epdf &	_epdf ()
	access function
Protected Attributes
double	l
	parameter l
vec	refl
	reference vector
egamma	epdf
	Internal epdf that arise by conditioning on `rvc`.
double	k
	Constant .
vec *	_beta
	cache of epdf.beta
RV	rv
	modeled random variable
RV	rvc
	random variable in condition
epdf *	ep
	pointer to internal epdf