bdm::merger Class Reference

#include <merger.h>

Inheritance diagram for bdm::merger:

Detailed Description

Function for general combination of pdfs.

Mixtures of Gaussian densities are used internally. Switching to other densities should be trivial.

Public Member Functions

merger (const Array< mpdf * > &S)

Default constructor.

void set_parameters (double beta0, int Ns0, int Nc0)

Set internal parameters used in approximation.

void init ()

Initialize the proposal density. This function must be called before merge()!

void merge (const epdf *g0)

Create a mixture density using known proposal.

void merge ()

Create a mixture density, make sure to call init() before the first call.

vec lognorm_merge (mat &lW)

Merge log-likelihood values.

vec sample () const

double evallog (const vec &dt) const

Compute log-probability of argument val.

vec mean () const

return expected value

mat covariance () const

vec variance () const

return expected variance (not covariance!)

virtual ~merger ()

for future use

MixEF & _Mix ()

Access function.

eEmp & _Smp ()

Access function.

RV getrv (bool checkoverlap=false)

find common rv, flag

void setrvc (const RV &rv, RV &rvc)

common rvc of all mpdfs is written to rvc

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, $[x_1 , x_2 , \ldots \$ from density $ f_x(rv)$ .

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

MixEF Mix

Internal mixture of EF models.

Array< datalink_m2e * > dls

Data link for each mpdf in mpdfs.

Array< RV > rvzs

Array of rvs that are not modelled by mpdfs at all (aux).

Array< datalink_m2e * > zdls

Data Links of rv0 mpdfs - these will be conditioned the (rv,rvc) of mpdfs.

int Ns

Number of samples used in approximation.

int Nc

Number of components in a mixture.

double beta

Prior on the log-normal merging model.

eEmp eSmp

Projection to empirical density.

int n

Number of mpdfs in the composite.

Array< mpdf * > mpdfs

Elements of composition.

int dim

dimension of the random variable

RV rv

Description of the random variable.

Member Function Documentation

vec bdm::merger::sample ( ) const [inline, virtual]

sample from merged density weight w is a

Reimplemented from bdm::epdf.

References Mix, bdm::MixEF::posterior(), and bdm::epdf::sample().

RV bdm::compositepdf::getrv ( bool checkoverlap = false ) [inherited]

find common rv, flag

Parameters:

checkoverlap

modifies whether overlaps are acceptable

References bdm::RV::add(), bdm::compositepdf::mpdfs, and bdm::compositepdf::n.

Referenced by bdm::mprod::mprod().

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

merger.h
merger.cpp


Public Member Functions
	merger (const Array< mpdf * > &S)
	Default constructor.
void	set_parameters (double beta0, int Ns0, int Nc0)
	Set internal parameters used in approximation.
void	init ()
	Initialize the proposal density. This function must be called before merge()!
void	merge (const epdf *g0)
	Create a mixture density using known proposal.
void	merge ()
	Create a mixture density, make sure to call init() before the first call.
vec	lognorm_merge (mat &lW)
	Merge log-likelihood values.
vec	sample () const
double	evallog (const vec &dt) const
	Compute log-probability of argument `val`.
vec	mean () const
	return expected value
mat	covariance () const
vec	variance () const
	return expected variance (not covariance!)
virtual	~merger ()
	for future use
MixEF &	_Mix ()
	Access function.
eEmp &	_Smp ()
	Access function.
RV	getrv (bool checkoverlap=false)
	find common rv, flag
void	setrvc (const RV &rv, RV &rvc)
	common rvc of all mpdfs is written to rvc
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, $[x_1 , x_2 , \ldots \$ 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
MixEF	Mix
	Internal mixture of EF models.
Array< datalink_m2e * >	dls
	Data link for each mpdf in mpdfs.
Array< RV >	rvzs
	Array of rvs that are not modelled by mpdfs at all (aux).
Array< datalink_m2e * >	zdls
	Data Links of rv0 mpdfs - these will be conditioned the (rv,rvc) of mpdfs.
int	Ns
	Number of samples used in approximation.
int	Nc
	Number of components in a mixture.
double	beta
	Prior on the log-normal merging model.
eEmp	eSmp
	Projection to empirical density.
int	n
	Number of mpdfs in the composite.
Array< mpdf * >	mpdfs
	Elements of composition.
int	dim
	dimension of the random variable
RV	rv
	Description of the random variable.