com.mockturtlesolutions.snifflib.stats

Class NormalDistribution

java.lang.Object

com.mockturtlesolutions.snifflib.stats.ProbabilityDensity

com.mockturtlesolutions.snifflib.stats.NormalDistribution

All Implemented Interfaces:

NamedParameters, OptimizableScalar, CDF, InvCDF

public class NormalDistribution
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
NormalDistribution()
NormalDistribution(DblMatrix mu, DblMatrix sigma)
NormalDistribution(DblMatrix mu, double sigma)
NormalDistribution(double mu, DblMatrix sigma)
NormalDistribution(double mu, double sigma)
NormalDistribution(int mu, int sigma)

Method Summary

Methods

Modifier and Type	Method and Description
DblMatrix	cdf(DblMatrix xx) CDF of the Normal distribution.
DblMatrix	cdf(double xx)
DblMatrix	cdf(java.lang.Double xx)
DblMatrix	criticalValue(DblMatrix p) For an input value C returns x such that P(X<=x) = C.
DblMatrix	criticalValue(double xx)
DblMatrix	criticalValue(java.lang.Double xx)
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	pdf(double xx)
DblMatrix	pdf(java.lang.Double xx)
DblMatrix	random(int N) Return N random draws from this distribution.
void	setMean(DblMatrix u)
void	setStd(DblMatrix sig)
void	setVariable(DblMatrix ff)
void	setVariance(DblMatrix sigsq)
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

NormalDistribution

public NormalDistribution()

NormalDistribution

public NormalDistribution(DblMatrix mu,
                  DblMatrix sigma)

NormalDistribution

public NormalDistribution(double mu,
                  DblMatrix sigma)

NormalDistribution

public NormalDistribution(DblMatrix mu,
                  double sigma)

NormalDistribution

public NormalDistribution(double mu,
                  double sigma)

NormalDistribution

public NormalDistribution(int mu,
                  int sigma)

Method Detail

random

public DblMatrix random(int N)

Return N random draws from this distribution.

Overrides:

random in class ProbabilityDensity

setMean

public void setMean(DblMatrix u)

setStd

public void setStd(DblMatrix sig)

setVariance

public void setVariance(DblMatrix sigsq)

setVariable

public void setVariable(DblMatrix ff)

getVariable

public DblMatrix getVariable()

criticalValue

public DblMatrix criticalValue(double xx)

criticalValue

public DblMatrix criticalValue(java.lang.Double xx)

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(double xx)

pdf

public DblMatrix pdf(java.lang.Double xx)

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(double xx)

cdf

public DblMatrix cdf(java.lang.Double xx)

cdf

public DblMatrix cdf(DblMatrix xx)

CDF of the Normal distribution.

Specified by:

cdf in interface CDF

Specified by:

cdf in class ProbabilityDensity