PLearn::ConcatColumnsRandomVariable Class Reference

concatenate the columns of the matrix arguments, just like the hconcat function (PLearn.h) on Vars. More...

#include <RandomVar.h>

Inheritance diagram for PLearn::ConcatColumnsRandomVariable:

[legend]Collaboration diagram for PLearn::ConcatColumnsRandomVariable:

[legend]List of all members.

Public Member Functions
	ConcatColumnsRandomVariable (const RVArray &vars)
	ConcatColumnsRandomVariable *.
virtual char *	classname ()
void	setValueFromParentsValue ()
	set the field value from the values of the parents
bool	invertible (const Var &obs, RVInstanceArray &unobserved_parents, Var **JacobianCorrection)
	!< SUBCLASS WRITERS: IMPLEMENT FUNCTIONS BELOW //!<
void	EMBprop (const Vec obs, real posterior)

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Detailed Description

concatenate the columns of the matrix arguments, just like the hconcat function (PLearn.h) on Vars.

Definition at line 1521 of file RandomVar.h.

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Constructor & Destructor Documentation

PLearn::ConcatColumnsRandomVariable::ConcatColumnsRandomVariable (  const RVArray &  a  )

ConcatColumnsRandomVariable *. Definition at line 2368 of file RandomVar.cc. References setValueFromParentsValue().

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Member Function Documentation

virtual char* PLearn::ConcatColumnsRandomVariable::classname (   )  [inline, virtual]

Implements PLearn::RandomVariable. Definition at line 1525 of file RandomVar.h.

void PLearn::ConcatColumnsRandomVariable::EMBprop (  const Vec  obs, real  posterior )  [virtual]

************ EM STUFF ********** propagate posterior information to parents in order to perform an EMupdate at the end of an EMEpoch. In the case of mixture-like RVs and their components, the posterior is the probability of the component "this" given the observation "obs". Implements PLearn::RandomVariable. Definition at line 2392 of file RandomVar.cc. References PLERROR, and PLearn::Vec.

bool PLearn::ConcatColumnsRandomVariable::invertible (  const Var &  obs, RVInstanceArray &  unobserved_parents, Var **  JacobianCorrection )  [virtual]

!< SUBCLASS WRITERS: IMPLEMENT FUNCTIONS BELOW //!< check whether it is possible to invert the function which maps the given unobserved parents to the observed value of the RV (obs). If invertible, do the inversion, and set the value fields of the RVInstances to Var's which are functionally dependent on obs. If the absolute value of the Jacobian of the map from the unobserved parents to this R.V.'s value is different from 1, then JacobianCorrection should point to a Var that is the logarithm of the determinant of this Jacobian (first derivatives) matrix. If the function is not invertible but it is possible to write P(Y==obs | unobserved_parents) in terms of the unobserved_parents logP functions, then the sub-class writer should instead redefine the logP function appropriately. Reimplemented from PLearn::FunctionalRandomVariable. Definition at line 2385 of file RandomVar.cc. References PLERROR.

void PLearn::ConcatColumnsRandomVariable::setValueFromParentsValue (   )  [virtual]

set the field value from the values of the parents Implements PLearn::FunctionalRandomVariable. Definition at line 2378 of file RandomVar.cc. References PLearn::hconcat(), and PLearn::RVArray::values(). Referenced by ConcatColumnsRandomVariable().

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

• RandomVar.h
• RandomVar.cc

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