PLearn::DiagonalNormalRandomVariable Class Reference

#include <RandomVar.h>

Inheritance diagram for PLearn::DiagonalNormalRandomVariable:

[legend]Collaboration diagram for PLearn::DiagonalNormalRandomVariable:

[legend]List of all members.

Public Member Functions
	DiagonalNormalRandomVariable (const RandomVar &mean, const RandomVar &log_variance, real minimum_standard_deviation=1e-10)
	DiagonalNormalRandomVariable *.
virtual char *	classname ()
Var	logP (const Var &obs, const RVInstanceArray &RHS, RVInstanceArray *parameters_to_learn)
void	setValueFromParentsValue ()
void	EMUpdate ()
void	EMBprop (const Vec obs, real posterior)
void	EMEpochInitialize ()
	Initialization of an individual EMEpoch.
const RandomVar &	mean ()
	convenience inlines
const RandomVar &	log_variance ()
bool &	learn_the_mean ()
bool &	learn_the_variance ()
Protected Attributes
real	minimum_variance
real	normfactor
	normalization constant = dimension * log(2 PI)
bool	shared_variance
	iff log_variance->length()==1
Vec	mu_num
	numerator for mean update in EM algorithm
Vec	sigma_num
	numerator for variance update in EM algorithm
real	denom
	denominator for mean and variance update in EM algorithm

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Constructor & Destructor Documentation

PLearn::DiagonalNormalRandomVariable::DiagonalNormalRandomVariable (  const RandomVar &  mean, const RandomVar &  log_var, real  minimum_standard_deviation = 1e-10 )

DiagonalNormalRandomVariable *. Definition at line 1855 of file RandomVar.cc. References Log2Pi, and PLearn::mean().

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Member Function Documentation

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

Implements PLearn::RandomVariable. Definition at line 1221 of file RandomVar.h.

void PLearn::DiagonalNormalRandomVariable::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 1913 of file RandomVar.cc. References PLearn::apply(), denom, PLearn::diffSquareMultiplyAcc(), PLearn::exp(), learn_the_mean(), learn_the_variance(), PLearn::RandomVariable::length(), log_variance(), mean(), minimum_variance, mu_num, PLearn::multiplyAcc(), PLERROR, PLearn::powdistance(), PLearn::pownorm(), shared_variance, sigma_num, PLearn::square_f(), PLearn::squareMultiplyAcc(), PLearn::substract(), and PLearn::Vec.

void PLearn::DiagonalNormalRandomVariable::EMEpochInitialize (   )  [virtual]

Initialization of an individual EMEpoch. the default just propagates to the unmarked parents Reimplemented from PLearn::RandomVariable. Definition at line 1902 of file RandomVar.cc. References PLearn::TVec< T >::clear(), denom, learn_the_mean(), learn_the_variance(), mu_num, and sigma_num.

void PLearn::DiagonalNormalRandomVariable::EMUpdate (   )  [virtual]

update the fixed (non-random) parameters using internal learning mechanism, at end of an EMEpoch. the default just propagates to the unmarked parents. Reimplemented from PLearn::RandomVariable. Definition at line 1964 of file RandomVar.cc. References PLearn::apply(), denom, learn_the_mean(), learn_the_variance(), log_variance(), PLearn::max(), PLearn::mean(), mean(), minimum_variance, mu_num, PLearn::multiply(), PLearn::mv(), PLearn::safeflog(), shared_variance, sigma_num, and PLearn::substract().

bool& PLearn::DiagonalNormalRandomVariable::learn_the_mean (   )  [inline]

Definition at line 1233 of file RandomVar.h. Referenced by EMBprop(), EMEpochInitialize(), and EMUpdate().

bool& PLearn::DiagonalNormalRandomVariable::learn_the_variance (   )  [inline]

Definition at line 1234 of file RandomVar.h. Referenced by EMBprop(), EMEpochInitialize(), and EMUpdate().

const RandomVar& PLearn::DiagonalNormalRandomVariable::log_variance (   )  [inline]

Definition at line 1232 of file RandomVar.h. Referenced by EMBprop(), EMUpdate(), logP(), and setValueFromParentsValue().

Var PLearn::DiagonalNormalRandomVariable::logP (  const Var &  obs, const RVInstanceArray &  RHS, RVInstanceArray *  parameters_to_learn )  [virtual]

Construct a Var that computes logP(This = obs | RHS ). This function SHOULD NOT be used directly, but is called by the global function logP (same argument), which does proper massaging of the network before and after this call. Implements PLearn::RandomVariable. Definition at line 1864 of file RandomVar.cc. References PLearn::exp(), PLearn::log(), log_variance(), PLearn::logP(), PLearn::marginalize(), mean(), minimum_variance, normfactor, shared_variance, PLearn::square(), PLearn::sum(), and PLearn::variance().

const RandomVar& PLearn::DiagonalNormalRandomVariable::mean (   )  [inline]

convenience inlines Definition at line 1231 of file RandomVar.h. Referenced by EMBprop(), EMUpdate(), logP(), and setValueFromParentsValue().

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

define the formula that gives a value to this RV given its parent's value (sets the value field). If the RV is stochastic, the formula may also be "stochastic" (using SampleVariable's to define the Var). Implements PLearn::RandomVariable. Definition at line 1894 of file RandomVar.cc. References PLearn::exp(), log_variance(), mean(), minimum_variance, and PLearn::sqrt().

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Member Data Documentation

real PLearn::DiagonalNormalRandomVariable::denom [protected]

denominator for mean and variance update in EM algorithm Definition at line 1240 of file RandomVar.h. Referenced by EMBprop(), EMEpochInitialize(), and EMUpdate().

real PLearn::DiagonalNormalRandomVariable::minimum_variance [protected]

mean = parents[0] log_variance = parents[1] variance = minimum_variance + exp(log_variance); Definition at line 1212 of file RandomVar.h. Referenced by EMBprop(), EMUpdate(), logP(), and setValueFromParentsValue().

Vec PLearn::DiagonalNormalRandomVariable::mu_num [protected]

numerator for mean update in EM algorithm Definition at line 1238 of file RandomVar.h. Referenced by EMBprop(), EMEpochInitialize(), and EMUpdate().

real PLearn::DiagonalNormalRandomVariable::normfactor [protected]

normalization constant = dimension * log(2 PI) Definition at line 1213 of file RandomVar.h. Referenced by logP().

bool PLearn::DiagonalNormalRandomVariable::shared_variance [protected]

iff log_variance->length()==1 Definition at line 1214 of file RandomVar.h. Referenced by EMBprop(), EMUpdate(), and logP().

Vec PLearn::DiagonalNormalRandomVariable::sigma_num [protected]

numerator for variance update in EM algorithm Definition at line 1239 of file RandomVar.h. Referenced by EMBprop(), EMEpochInitialize(), and EMUpdate().

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

• RandomVar.h
• RandomVar.cc

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