Package org.ojalgo.random
Class TDistribution
java.lang.Object
org.ojalgo.random.RandomNumber
org.ojalgo.random.AbstractContinuous
org.ojalgo.random.TDistribution
- All Implemented Interfaces:
Comparable<RandomNumber>
,DoubleSupplier
,Supplier<Double>
,BasicFunction
,NullaryFunction<Double>
,PrimitiveFunction.Nullary
,ContinuousDistribution
,Distribution
,AccessScalar<Double>
,ComparableNumber<RandomNumber>
,NumberDefinition
- Direct Known Subclasses:
TDistribution.Degree1
,TDistribution.Degree2
,TDistribution.Degree3
,TDistribution.Degree4
,TDistribution.Degree5
,TDistribution.DegreeInfinity
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Nested Class Summary
Nested ClassesModifier and TypeClassDescription(package private) static final class
(package private) static final class
(package private) static final class
(package private) static final class
(package private) static final class
(package private) static final class
Nested classes/interfaces inherited from interface org.ojalgo.function.BasicFunction
BasicFunction.Differentiable<N extends Comparable<N>,
F extends BasicFunction>, BasicFunction.Integratable<N extends Comparable<N>, F extends BasicFunction>, BasicFunction.PlainUnary<T, R> -
Field Summary
FieldsModifier and TypeFieldDescriptionprivate static final double
private final double
The density and distribution functions share a common constant factorprivate final double
private static final Normal
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionprivate double
approximateQuantile
(double probability) double
getDensity
(double value) In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point.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
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
Subclasses must override either getStandardDeviation() or getVariance()!static TDistribution
of
(int degreesOfFreedom) static TDistribution
Methods inherited from class org.ojalgo.random.AbstractContinuous
generate
Methods inherited from class org.ojalgo.random.RandomNumber
checkProbabilty, compareTo, doubleValue, floatValue, getStandardDeviation, intValue, invoke, longValue, newSampleSet, random, setRandom, setSeed, toString
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
Methods inherited from interface org.ojalgo.random.ContinuousDistribution
getLowerConfidenceQuantile, getUpperConfidenceQuantile
Methods inherited from interface org.ojalgo.random.Distribution
getStandardDeviation
Methods inherited from interface org.ojalgo.function.NullaryFunction
andThen, get, getAsDouble
Methods inherited from interface org.ojalgo.type.NumberDefinition
booleanValue, byteValue, shortValue
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Field Details
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_0_0001
private static final double _0_0001- See Also:
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NORMAL
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myConstant
private final double myConstantThe density and distribution functions share a common constant factor -
myDegreesOfFreedom
private final double myDegreesOfFreedom
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Constructor Details
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TDistribution
TDistribution(double degreesOfFreedom)
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Method Details
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of
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ofInfinity
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getDensity
public double getDensity(double value) Description copied from interface:ContinuousDistribution
In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point. The probability for the random variable to fall within a particular region is given by the integral of this variable's density over the region. The probability density function is nonnegative everywhere, and its integral over the entire space is equal to one. WikipediA- Parameters:
value
- x- Returns:
- P(x)
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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- Parameters:
value
- x- Returns:
- P(≤x)
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getExpected
public double getExpected() -
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- Parameters:
probability
- P(<=x)- Returns:
- x
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getVariance
public double getVariance()Description copied from class:RandomNumber
Subclasses must override either getStandardDeviation() or getVariance()!- Specified by:
getVariance
in interfaceDistribution
- Overrides:
getVariance
in classRandomNumber
- See Also:
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approximateQuantile
private double approximateQuantile(double probability)
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