Package org.ojalgo.random
Class TDistribution.DegreeInfinity
- java.lang.Object
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- org.ojalgo.random.RandomNumber
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- org.ojalgo.random.AbstractContinuous
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- org.ojalgo.random.TDistribution
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- org.ojalgo.random.TDistribution.DegreeInfinity
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- All Implemented Interfaces:
java.lang.Comparable<RandomNumber>
,java.util.function.DoubleSupplier
,java.util.function.Supplier<java.lang.Double>
,BasicFunction
,NullaryFunction<java.lang.Double>
,PrimitiveFunction.Nullary
,ContinuousDistribution
,Distribution
,AccessScalar<java.lang.Double>
,ComparableNumber<RandomNumber>
,NumberDefinition
- Enclosing class:
- TDistribution
static final class TDistribution.DegreeInfinity extends TDistribution
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Nested Class Summary
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Nested classes/interfaces inherited from class org.ojalgo.random.TDistribution
TDistribution.Degree1, TDistribution.Degree2, TDistribution.Degree3, TDistribution.Degree4, TDistribution.Degree5, TDistribution.DegreeInfinity
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Nested classes/interfaces inherited from interface org.ojalgo.function.BasicFunction
BasicFunction.Differentiable<N extends java.lang.Comparable<N>,F extends BasicFunction>, BasicFunction.Integratable<N extends java.lang.Comparable<N>,F extends BasicFunction>, BasicFunction.PlainUnary<T,R>
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Constructor Summary
Constructors Constructor Description DegreeInfinity()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description protected double
generate()
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
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.-
Methods inherited from class org.ojalgo.random.TDistribution
getExpected, getVariance, of, ofInfinity
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Methods inherited from class org.ojalgo.random.RandomNumber
checkProbabilty, compareTo, doubleValue, floatValue, getStandardDeviation, intValue, invoke, longValue, newSampleSet, random, setRandom, setSeed, toString
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Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
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Methods inherited from interface org.ojalgo.random.ContinuousDistribution
getLowerConfidenceQuantile, getUpperConfidenceQuantile
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Methods inherited from interface org.ojalgo.random.Distribution
getStandardDeviation
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Methods inherited from interface org.ojalgo.function.NullaryFunction
andThen, get, getAsDouble
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Methods inherited from interface org.ojalgo.type.NumberDefinition
booleanValue, byteValue, shortValue
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Field Detail
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myNormal
private final Normal myNormal
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Method Detail
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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- Specified by:
getDensity
in interfaceContinuousDistribution
- Overrides:
getDensity
in classTDistribution
- 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- Specified by:
getDistribution
in interfaceContinuousDistribution
- Overrides:
getDistribution
in classTDistribution
- Parameters:
value
- x- Returns:
- P(≤x)
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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 interfaceContinuousDistribution
- Overrides:
getQuantile
in classTDistribution
- Parameters:
probability
- P(<=x)- Returns:
- x
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generate
protected double generate()
- Overrides:
generate
in classAbstractContinuous
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