Class Gamma
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- All Implemented Interfaces:
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java.io.Serializable,jline.lang.Copyable
public class Gamma extends ContinuousDistribution implements Serializable
A Gamma distribution.
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Constructor Summary
Constructors Constructor Description Gamma(double shape, double scale)
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Method Summary
Modifier and Type Method Description static GammafitMeanAndSCV(double mean, double scv)doubleevalCDF(double t)Evaluates the cumulative distribution function (CDF) at the given point. doubleevalLST(double s)Evaluate the Laplace-Stieltjes Transform at s doublegetMean()Gets the mean (expected value) of this distribution. doublegetRate()Gets the rate of this distribution (inverse of mean). doublegetSCV()Gets the squared coefficient of variation (SCV) of this distribution. doublegetSkewness()Gets the skewness of this distribution. doublegetVar()Gets the variance of this distribution. Array<double>sample(int n, Random random)Generates random samples from this distribution using the specified random generator. Array<double>sample(int n)Generates random samples from this distribution using default random generator. MatrixCellgetProcess()MatrixCellprocess()Kotlin-style property alias for getProcess() doublemean()Kotlin-style property alias for getMean() doublerate()Kotlin-style property alias for getRate() doublescv()Kotlin-style property alias for getSCV() doubleskewness()Kotlin-style property alias for getSkewness() doublevar()Kotlin-style property alias for getVar() -
Methods inherited from class jline.lang.processes.Distribution
evalProbInterval, getName, getNumParams, getParam, getSupport, isContinuous, isDisabled, isDiscrete, isImmediate, isMarkovian, name, numParams, param, setNumParams, setParam, support -
Methods inherited from class jline.lang.Copyable
copy -
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Method Detail
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fitMeanAndSCV
static Gamma fitMeanAndSCV(double mean, double scv)
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evalCDF
double evalCDF(double t)
Evaluates the cumulative distribution function (CDF) at the given point.
- Parameters:
t- the point at which to evaluate the CDF- Returns:
the CDF value at point t
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evalLST
double evalLST(double s)
Evaluate the Laplace-Stieltjes Transform at s
- Parameters:
s- the Laplace domain variable- Returns:
the LST value at s
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getMean
double getMean()
Gets the mean (expected value) of this distribution.
- Returns:
the mean value
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getRate
double getRate()
Gets the rate of this distribution (inverse of mean).
- Returns:
the rate value (1/mean)
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getSCV
double getSCV()
Gets the squared coefficient of variation (SCV) of this distribution. SCV = Var(X) / E[X]^2.
- Returns:
the squared coefficient of variation
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getSkewness
double getSkewness()
Gets the skewness of this distribution. Skewness measures the asymmetry of the probability distribution.
- Returns:
the skewness value
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getVar
double getVar()
Gets the variance of this distribution. Computed as SCV * mean^2.
- Returns:
the variance
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sample
Array<double> sample(int n, Random random)
Generates random samples from this distribution using the specified random generator.
- Parameters:
n- the number of samples to generaterandom- the random number generator to use- Returns:
array of random samples
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sample
Array<double> sample(int n)
Generates random samples from this distribution using default random generator.
- Parameters:
n- the number of samples to generate- Returns:
array of random samples
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getProcess
MatrixCell getProcess()
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process
MatrixCell process()
Kotlin-style property alias for getProcess()
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mean
double mean()
Kotlin-style property alias for getMean()
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rate
double rate()
Kotlin-style property alias for getRate()
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scv
double scv()
Kotlin-style property alias for getSCV()
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skewness
double skewness()
Kotlin-style property alias for getSkewness()
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var
double var()
Kotlin-style property alias for getVar()
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