com.mockturtlesolutions.snifflib.stats

Class UniformDistribution

java.lang.Object

com.mockturtlesolutions.snifflib.stats.ProbabilityDensity

com.mockturtlesolutions.snifflib.stats.UniformDistribution

All Implemented Interfaces:

NamedParameters, OptimizableScalar, CDF, InvCDF

public class UniformDistribution
extends ProbabilityDensity

Field Summary

Fields inherited from class com.mockturtlesolutions.snifflib.stats.ProbabilityDensity

GET_CDF, GET_ICDF, GET_PDF

Constructor Summary

Constructors

Constructor and Description
UniformDistribution()
UniformDistribution(DblMatrix low, DblMatrix high)
UniformDistribution(DblMatrix low, double high)
UniformDistribution(double low, DblMatrix high)
UniformDistribution(double low, double high)
UniformDistribution(int low, int high)

Method Summary

Methods

Modifier and Type	Method and Description
DblMatrix	cdf(DblMatrix xx) CDF of the Normal distribution.
DblMatrix	criticalValue(DblMatrix p) For an input value C returns x such that P(X<=x) = C.
DblMatrix	getVariable()
DblMatrix	hasSupport(DblMatrix X) Returns 1 if the density has the input value in its support set (domain) and 0 otherwise.
DblMatrix	mean() Returns the expected value of the distribution for the currently configured parameters.
DblMatrix	pdf(DblMatrix X) Returns the value of the density function at X.
DblMatrix	random(int N) Return N random draws from this distribution.
DblMatrix	random(int[] N) Return matrix of the given size containing random draws from this distribution.
void	setHigh(DblMatrix b)
void	setLow(DblMatrix a)
void	setVariable(DblMatrix ff)
DblMatrix	variance() Returns the expected value of the distribution for the currently configured parameters.

Methods inherited from class com.mockturtlesolutions.snifflib.stats.ProbabilityDensity

assumeProbability, getAssumedProbability, getName, getParam, getParams, getValueAt, getValueToGet, getValueToMinimize, getVariableValue, hasParameter, parameterSet, replaceParams, setName, setParam, setValueToGet, setVariableValue

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

UniformDistribution

public UniformDistribution()

UniformDistribution

public UniformDistribution(DblMatrix low,
                   DblMatrix high)

UniformDistribution

public UniformDistribution(double low,
                   DblMatrix high)

UniformDistribution

public UniformDistribution(DblMatrix low,
                   double high)

UniformDistribution

public UniformDistribution(double low,
                   double high)

UniformDistribution

public UniformDistribution(int low,
                   int high)

Method Detail

random

public DblMatrix random(int N)

Return N random draws from this distribution.

Overrides:

random in class ProbabilityDensity

random

public DblMatrix random(int[] N)

Return matrix of the given size containing random draws from this distribution.

setLow

public void setLow(DblMatrix a)

setHigh

public void setHigh(DblMatrix b)

setVariable

public void setVariable(DblMatrix ff)

getVariable

public DblMatrix getVariable()

criticalValue

public DblMatrix criticalValue(DblMatrix p)

For an input value C returns x such that P(X<=x) = C. This is the inverse CDF of the distribution.

Specified by:

criticalValue in interface InvCDF

Specified by:

criticalValue in class ProbabilityDensity

pdf

public DblMatrix pdf(DblMatrix X)

Returns the value of the density function at X.

Specified by:

pdf in class ProbabilityDensity

hasSupport

public DblMatrix hasSupport(DblMatrix X)

Description copied from class: ProbabilityDensity

Returns 1 if the density has the input value in its support set (domain) and 0 otherwise.

Specified by:

hasSupport in class ProbabilityDensity

mean

public DblMatrix mean()

Returns the expected value of the distribution for the currently configured parameters.

variance

public DblMatrix variance()

Returns the expected value of the distribution for the currently configured parameters.

cdf

public DblMatrix cdf(DblMatrix xx)

CDF of the Normal distribution.

Specified by:

cdf in interface CDF

Specified by:

cdf in class ProbabilityDensity