Class AbstractContinuousDistribution
- java.lang.Object
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- org.apache.commons.math.distribution.AbstractDistribution
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- org.apache.commons.math.distribution.AbstractContinuousDistribution
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- All Implemented Interfaces:
java.io.Serializable
,ContinuousDistribution
,Distribution
- Direct Known Subclasses:
BetaDistributionImpl
,CauchyDistributionImpl
,ChiSquaredDistributionImpl
,ExponentialDistributionImpl
,FDistributionImpl
,GammaDistributionImpl
,NormalDistributionImpl
,TDistributionImpl
,WeibullDistributionImpl
public abstract class AbstractContinuousDistribution extends AbstractDistribution implements ContinuousDistribution, java.io.Serializable
Base class for continuous distributions. Default implementations are provided for some of the methods that do not vary from distribution to distribution.- See Also:
- Serialized Form
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
density(double x)
Return the probability density for a particular point.double
inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such that P(X < x) =p
.void
reseedRandomGenerator(long seed)
Reseeds the random generator used to generate samples.double
sample()
Generates a random value sampled from this distribution.double[]
sample(int sampleSize)
Generates a random sample from the distribution.-
Methods inherited from class org.apache.commons.math.distribution.AbstractDistribution
cumulativeProbability
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Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface org.apache.commons.math.distribution.Distribution
cumulativeProbability, cumulativeProbability
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Method Detail
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density
public double density(double x) throws MathRuntimeException
Return the probability density for a particular point.- Parameters:
x
- The point at which the density should be computed.- Returns:
- The pdf at point x.
- Throws:
MathRuntimeException
- if the specialized class hasn't implemented this function- Since:
- 2.1
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inverseCumulativeProbability
public double inverseCumulativeProbability(double p) throws MathException
For this distribution, X, this method returns the critical point x, such that P(X < x) =p
.- Specified by:
inverseCumulativeProbability
in interfaceContinuousDistribution
- Parameters:
p
- the desired probability- Returns:
- x, such that P(X < x) =
p
- Throws:
MathException
- if the inverse cumulative probability can not be computed due to convergence or other numerical errors.java.lang.IllegalArgumentException
- ifp
is not a valid probability.
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reseedRandomGenerator
public void reseedRandomGenerator(long seed)
Reseeds the random generator used to generate samples.- Parameters:
seed
- the new seed- Since:
- 2.2
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sample
public double sample() throws MathException
Generates a random value sampled from this distribution. The default implementation uses the inversion method.- Returns:
- random value
- Throws:
MathException
- if an error occurs generating the random value- Since:
- 2.2
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sample
public double[] sample(int sampleSize) throws MathException
Generates a random sample from the distribution. The default implementation generates the sample by callingsample()
in a loop.- Parameters:
sampleSize
- number of random values to generate- Returns:
- an array representing the random sample
- Throws:
MathException
- if an error occurs generating the samplejava.lang.IllegalArgumentException
- if sampleSize is not positive- Since:
- 2.2
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