pf::filters::multivGamFilter< dim_obs, dim_pred, float_t > Class Template Reference

Another class template for Gamma filtering, but this time. More...

#include <cf_filters.h>

Inheritance diagram for pf::filters::multivGamFilter< dim_obs, dim_pred, float_t >:

Collaboration diagram for pf::filters::multivGamFilter< dim_obs, dim_pred, float_t >:

Public Types
using	psv = Eigen::Matrix< float_t, dim_pred, 1 >
	"predictor size vector"
using	bsm = Eigen::Matrix< float_t, dim_obs, dim_pred >
	"beta size matrix"
using	tsv = Eigen::Matrix< float_t, 2, 1 >
	"two by 1 vector" to store size and shapes of gamma distributions
using	osv = Eigen::Matrix< float_t, dim_obs, 1 >
	"observation size vector"
using	osm = Eigen::Matrix< float_t, dim_obs, dim_obs >
	"observation size matrix"
Public Types inherited from pf::bases::cf_filter< 1, dim_obs, float_t >
using	obs_sized_vec = Eigen::Matrix< float_t, dimobs, 1 >
using	state_sized_vec = Eigen::Matrix< float_t, dimstate, 1 >

Public Member Functions
	multivGamFilter (const float_t &nOneTilde, const float_t &dOneTilde)
	Constructor. More...
virtual	~multivGamFilter ()
	The (virtual) desuctor.
float_t	getLogCondLike () const
	Get the latest conditional likelihood. More...
tsv	getFilterVec () const
	Get the current filter vector. More...
void	update (const osv &yt, const psv &xt, const bsm &B, const osm &Sigma, const float_t &delta)
	Perform a filtering update. More...
osv	getFcastMean (const psv &xtp1, const bsm &B, const osm &Sigma, const float_t &delta)
	Get the forecast mean (assuming filtering has been performed already) More...
osm	getFcastCov (const psv &xtp1, const bsm &B, const osm &Sigma, const float_t &delta)
	Get the forecast covariance matrix (assuming filtering has been performed already) More...
Public Member Functions inherited from pf::bases::cf_filter< 1, dim_obs, float_t >
virtual	~cf_filter ()
	The (virtual) destructor.
virtual float_t	getLogCondLike () const=0
	returns the log of the most recent conditional likelihood More...

Private Attributes
tsv	m_filtVec
	filter vector (shape and rate)
float_t	m_lastLogCondLike
	last log of the conditional likelihood
bool	m_fresh
	has data been observed?

Detailed Description

template<size_t dim_obs, size_t dim_pred, typename float_t>
class pf::filters::multivGamFilter< dim_obs, dim_pred, float_t >

Another class template for Gamma filtering, but this time.

Author

taylor

Constructor & Destructor Documentation

multivGamFilter()

template<size_t dim_obs, size_t dim_pred, typename float_t >

pf::filters::multivGamFilter< dim_obs, dim_pred, float_t >::multivGamFilter	(	const float_t &	nOneTilde,
		const float_t &	dOneTilde
	)

Constructor.

Parameters

nOneTilde	degrees of freedom for time 1 prior.
dOneTilde	rate parameter for time 1 prior.

Member Function Documentation

getFcastCov()

template<size_t dim_obs, size_t dim_pred, typename float_t >

auto pf::filters::multivGamFilter< dim_obs, dim_pred, float_t >::getFcastCov	(	const psv &	xtp1,
		const bsm &	B,
		const osm &	Sigma,
		const float_t &	delta
	)

Get the forecast covariance matrix (assuming filtering has been performed already)

gets the forecast covariance matrix!

Parameters

xtp1	the next time period's predictor vector
B	the loadings matrix
Sigma	the observation "shape" matrix
delta	between 0 and 1 the discount parameter

Returns

a forecast covariance matrix

getFcastMean()

template<size_t dim_obs, size_t dim_pred, typename float_t >

auto pf::filters::multivGamFilter< dim_obs, dim_pred, float_t >::getFcastMean	(	const psv &	xtp1,
		const bsm &	B,
		const osm &	Sigma,
		const float_t &	delta
	)

Get the forecast mean (assuming filtering has been performed already)

gets the forecast mean!

Parameters

xtp1	the next time period's predictor vector
B	the loadings matrix
Sigma	the observation "shape" matrix
delta	between 0 and 1 the discount parameter

Returns

a mean vector

getFilterVec()

template<size_t dim_obs, size_t dim_pred, typename float_t >

auto pf::filters::multivGamFilter< dim_obs, dim_pred, float_t >::getFilterVec

Get the current filter vector.

get the current filtering distribution. First element is the shape, second is the rate.

Returns

a vector of the shape and rate parameters of f(p_t | y_{1:t})

getLogCondLike()

template<size_t dim_obs, size_t dim_pred, typename float_t >

auto pf::filters::multivGamFilter< dim_obs, dim_pred, float_t >::getLogCondLike

Get the latest conditional likelihood.

Returns

the latest conditional likelihood.

update()

template<size_t dim_obs, size_t dim_pred, typename float_t >

void pf::filters::multivGamFilter< dim_obs, dim_pred, float_t >::update	(	const osv &	yt,
		const psv &	xt,
		const bsm &	B,
		const osm &	Sigma,
		const float_t &	delta
	)

Perform a filtering update.

Perform a Gamma filter update.

Parameters

yt	the most recent dependent random variable
xt	the most recent predictor vector
B	the loadings matrix
Sigma	the observation "shape" matrix.
delta	between 0 and 1 the discount parameter

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

• include/pf/cf_filters.h