edu::tum::cs::inference::BasicSampledDistribution Class Reference

Inheritance diagram for edu::tum::cs::inference::BasicSampledDistribution:

[legend]

List of all members.

Classes
class	ConfidenceInterval
class	DistributionComparison
class	DistributionEntryComparison
class	ErrorList
class	HellingerDistance
class	MeanSquaredError
Public Member Functions
	BasicSampledDistribution () throws Exception
double	compare (DistributionEntryComparison dec, BasicSampledDistribution otherDist) throws Exception
ConfidenceInterval	getConfidenceInterval (int varIdx, int domIdx)
double[]	getDistribution (int varIdx)
abstract String[]	getDomain (int idx)
int	getDomainSize (int idx)
double	getHellingerDistance (BasicSampledDistribution d) throws Exception
double	getMSE (BasicSampledDistribution d) throws Exception
abstract Integer	getNumSamples ()
ParameterHandler	getParameterHandler ()
double	getProbability (int varIdx, int domainIdx)
abstract int	getVariableIndex (String name)
abstract String	getVariableName (int idx)
void	print (PrintStream out)
void	printVariableDistribution (PrintStream out, int idx)
void	setConfidenceLevel (Double confidenceLevel)
GeneralSampledDistribution	toGeneralDistribution () throws Exception
boolean	usesConfidenceComputation ()
Public Attributes
Double	confidenceLevel = null
ParameterHandler	paramHandler
double[][]	values = null
Double	Z = null

---

Detailed Description

Definition at line 15 of file BasicSampledDistribution.java.

---

Constructor & Destructor Documentation

edu::tum::cs::inference::BasicSampledDistribution::BasicSampledDistribution

(

)

throws Exception [inline]

Definition at line 32 of file BasicSampledDistribution.java.

---

Member Function Documentation

double edu::tum::cs::inference::BasicSampledDistribution::compare	(	DistributionEntryComparison	dec,
		BasicSampledDistribution	otherDist
	)			throws Exception [inline]

Definition at line 111 of file BasicSampledDistribution.java.

ConfidenceInterval edu::tum::cs::inference::BasicSampledDistribution::getConfidenceInterval	(	int	varIdx,
		int	domIdx
	)			[inline]

Definition at line 74 of file BasicSampledDistribution.java.

double [] edu::tum::cs::inference::BasicSampledDistribution::getDistribution

(

int

varIdx

)

[inline]

constructs a new array with the normalized distribution over values for a variable

Parameters:

varIdx

index of the variable whose distribution to generate

Returns:

Definition at line 46 of file BasicSampledDistribution.java.

abstract String [] edu::tum::cs::inference::BasicSampledDistribution::getDomain

(

int

idx

)

[pure virtual]

Implemented in edu::tum::cs::bayesnets::inference::SampledDistribution, and edu::tum::cs::inference::GeneralSampledDistribution.

int edu::tum::cs::inference::BasicSampledDistribution::getDomainSize

(

int

idx

)

[inline]

Definition at line 82 of file BasicSampledDistribution.java.

double edu::tum::cs::inference::BasicSampledDistribution::getHellingerDistance

(

BasicSampledDistribution

d

)

throws Exception [inline]

Definition at line 107 of file BasicSampledDistribution.java.

double edu::tum::cs::inference::BasicSampledDistribution::getMSE

(

BasicSampledDistribution

d

)

throws Exception [inline]

gets the mean squared error of another distribution d, assuming that values of this distribution are correct

Parameters:

d

the other distribution

Returns:

the mean squared error (averaged across all entries of the distribution)

Exceptions:

Exception

Definition at line 103 of file BasicSampledDistribution.java.

abstract Integer edu::tum::cs::inference::BasicSampledDistribution::getNumSamples

(

)

[pure virtual]

Implemented in edu::tum::cs::bayesnets::inference::SampledDistribution, and edu::tum::cs::inference::GeneralSampledDistribution.

ParameterHandler edu::tum::cs::inference::BasicSampledDistribution::getParameterHandler

(

)

[inline]

Implements edu::tum::cs::inference::IParameterHandler.

Definition at line 126 of file BasicSampledDistribution.java.

double edu::tum::cs::inference::BasicSampledDistribution::getProbability	(	int	varIdx,
		int	domainIdx
	)			[inline]

Definition at line 37 of file BasicSampledDistribution.java.

abstract int edu::tum::cs::inference::BasicSampledDistribution::getVariableIndex

(

String

name

)

[pure virtual]

Implemented in edu::tum::cs::bayesnets::inference::SampledDistribution, and edu::tum::cs::inference::GeneralSampledDistribution.

abstract String edu::tum::cs::inference::BasicSampledDistribution::getVariableName

(

int

idx

)

[pure virtual]

Implemented in edu::tum::cs::bayesnets::inference::SampledDistribution, and edu::tum::cs::inference::GeneralSampledDistribution.

void edu::tum::cs::inference::BasicSampledDistribution::print

(

PrintStream

out

)

[inline]

Definition at line 53 of file BasicSampledDistribution.java.

void edu::tum::cs::inference::BasicSampledDistribution::printVariableDistribution	(	PrintStream	out,
		int	idx
	)			[inline]

Reimplemented in edu::tum::cs::bayesnets::inference::SampledDistribution.

Definition at line 61 of file BasicSampledDistribution.java.

void edu::tum::cs::inference::BasicSampledDistribution::setConfidenceLevel

(

Double

confidenceLevel

)

[inline]

Definition at line 118 of file BasicSampledDistribution.java.

GeneralSampledDistribution edu::tum::cs::inference::BasicSampledDistribution::toGeneralDistribution

(

)

throws Exception [inline]

Definition at line 86 of file BasicSampledDistribution.java.

boolean edu::tum::cs::inference::BasicSampledDistribution::usesConfidenceComputation

(

)

[inline]

Definition at line 122 of file BasicSampledDistribution.java.

---

Member Data Documentation

Double edu::tum::cs::inference::BasicSampledDistribution::confidenceLevel = null

the confidence level for the computation of confidence intervals if null, no confidence interval computations are carried out

Definition at line 29 of file BasicSampledDistribution.java.

ParameterHandler edu::tum::cs::inference::BasicSampledDistribution::paramHandler

Definition at line 30 of file BasicSampledDistribution.java.

double [][] edu::tum::cs::inference::BasicSampledDistribution::values = null

an array of values representing the distribution, one for each node and each domain element: values[i][j] is the value for the j-th domain element of the i-th node in the network

Definition at line 20 of file BasicSampledDistribution.java.

Double edu::tum::cs::inference::BasicSampledDistribution::Z = null

the normalization constant that applies to each of the distribution values

Definition at line 24 of file BasicSampledDistribution.java.

---

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

• BasicSampledDistribution.java