Class ChiSquareDistribution.NormalApproximation

java.lang.Object

org.ojalgo.random.RandomNumber

org.ojalgo.random.AbstractContinuous

org.ojalgo.random.ChiSquareDistribution

org.ojalgo.random.ChiSquareDistribution.NormalApproximation

All Implemented Interfaces:

Comparable<RandomNumber>, DoubleSupplier, Supplier<Double>, BasicFunction, NullaryFunction<Double>, PrimitiveFunction.Nullary, ContinuousDistribution, Distribution, AccessScalar<Double>, ComparableNumber<RandomNumber>, NumberDefinition

Enclosing class:

ChiSquareDistribution

static final class ChiSquareDistribution.NormalApproximation
extends ChiSquareDistribution

Nested Class Summary

Nested classes/interfaces inherited from class ChiSquareDistribution

ChiSquareDistribution.Degree2, ChiSquareDistribution.NormalApproximation

Nested classes/interfaces inherited from interface BasicFunction

BasicFunction.Differentiable<N,F>, BasicFunction.Integratable<N,F>, BasicFunction.PlainUnary<T,R>

Field Summary

Fields

Modifier and Type	Field	Description
private final Normal	myApproximation

Fields inherited from class ChiSquareDistribution

NORMAL

Constructor Summary

Constructors

Constructor	Description
NormalApproximation(double degreesOfFreedom)

Method Summary

Modifier and Type	Method	Description
(package private) double	calculateDensity(double value)
double	getDistribution(double value)	In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable X with a given probability distribution will be found at a value less than or equal to x.
double	getExpected()
double	getQuantile(double probability)	The quantile function, for any distribution, is defined for real variables between zero and one and is mathematically the inverse of the cumulative distribution function.
double	getStandardDeviation()	Subclasses must override either getStandardDeviation() or getVariance()!
double	getVariance()	Subclasses must override either getStandardDeviation() or getVariance()!

Methods inherited from class ChiSquareDistribution

getDensity, of

Methods inherited from class AbstractContinuous

generate

Methods inherited from class RandomNumber

checkProbabilty, compareTo, doubleValue, floatValue, intValue, invoke, longValue, newSampleSet, random, setRandom, setSeed, toString

Methods inherited from class Object

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

Methods inherited from interface ContinuousDistribution

getLowerConfidenceQuantile, getUpperConfidenceQuantile

Methods inherited from interface NullaryFunction

andThen, get, getAsDouble

Methods inherited from interface NumberDefinition

booleanValue, byteValue, shortValue

Field Details

myApproximation

private final Normal myApproximation

Constructor Details

NormalApproximation

NormalApproximation(double degreesOfFreedom)

Method Details

getDistribution

public double getDistribution(double value)

Description copied from interface: ContinuousDistribution

In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable X with a given probability distribution will be found at a value less than or equal to x. Intuitively, it is the "area so far" function of the probability distribution. Cumulative distribution functions are also used to specify the distribution of multivariate random variables. WikipediA

Specified by:

getDistribution in interface ContinuousDistribution

Overrides:

getDistribution in class ChiSquareDistribution

Parameters:

value - x

Returns:

P(≤x)

getExpected

public double getExpected()

Specified by:

getExpected in interface Distribution

Overrides:

getExpected in class ChiSquareDistribution

getQuantile

public double getQuantile(double probability)

Description copied from interface: ContinuousDistribution

The quantile function, for any distribution, is defined for real variables between zero and one and is mathematically the inverse of the cumulative distribution function. WikipediA The input probability absolutely has to be [0.0, 1.0], but values close to 0.0 and 1.0 may be problematic

Specified by:

getQuantile in interface ContinuousDistribution

Overrides:

getQuantile in class ChiSquareDistribution

Parameters:

probability - P(<=x)

Returns:

x

getStandardDeviation

public double getStandardDeviation()

Description copied from class: RandomNumber

Subclasses must override either getStandardDeviation() or getVariance()!

Specified by:

getStandardDeviation in interface Distribution

Overrides:

getStandardDeviation in class RandomNumber

See Also:

• Distribution.getStandardDeviation()
• Distribution.getVariance()

getVariance

public double getVariance()

Description copied from class: RandomNumber

Subclasses must override either getStandardDeviation() or getVariance()!

Specified by:

getVariance in interface Distribution

Overrides:

getVariance in class ChiSquareDistribution

See Also:

• Distribution.getStandardDeviation()
• Distribution.getVariance()

calculateDensity

double calculateDensity(double value)

Overrides:

calculateDensity in class ChiSquareDistribution