public class EnumeratedRealDistribution extends AbstractRealDistribution
Implementation of a real-valued EnumeratedDistribution.
 
Values with zero-probability are allowed but they do not extend the
 support.
 Duplicate values are allowed. Probabilities of duplicate values are combined
 when computing cumulative probabilities and statistics.
| Modifier and Type | Field and Description | 
|---|---|
| protected EnumeratedDistribution<Double> | innerDistributionEnumeratedDistribution(using theDoublewrapper)
 used to generate the pmf. | 
random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY| Constructor and Description | 
|---|
| EnumeratedRealDistribution(double[] data)Create a discrete real-valued distribution from the input data. | 
| EnumeratedRealDistribution(double[] singletons,
                          double[] probabilities)Create a discrete real-valued distribution using the given probability mass function
 enumeration. | 
| EnumeratedRealDistribution(RandomGenerator rng,
                          double[] data)Create a discrete real-valued distribution from the input data. | 
| EnumeratedRealDistribution(RandomGenerator rng,
                          double[] singletons,
                          double[] probabilities)Create a discrete real-valued distribution using the given random number generator
 and probability mass function enumeration. | 
| Modifier and Type | Method and Description | 
|---|---|
| double | cumulativeProbability(double x)For a random variable  Xwhose values are distributed according
 to this distribution, this method returnsP(X <= x). | 
| double | density(double x)For a random variable  Xwhose values are distributed according to
 this distribution, this method returnsP(X = x). | 
| double | getNumericalMean()Use this method to get the numerical value of the mean of this
 distribution. | 
| double | getNumericalVariance()Use this method to get the numerical value of the variance of this
 distribution. | 
| double | getSupportLowerBound()Access the lower bound of the support. | 
| double | getSupportUpperBound()Access the upper bound of the support. | 
| double | inverseCumulativeProbability(double p)Computes the quantile function of this distribution. | 
| boolean | isSupportConnected()Use this method to get information about whether the support is connected,
 i.e. | 
| boolean | isSupportLowerBoundInclusive()Whether or not the lower bound of support is in the domain of the density
 function. | 
| boolean | isSupportUpperBoundInclusive()Whether or not the upper bound of support is in the domain of the density
 function. | 
| double | probability(double x)For a random variable  Xwhose values are distributed according
 to this distribution, this method returnsP(X = x). | 
| double | sample()Generate a random value sampled from this distribution. | 
cumulativeProbability, getSolverAbsoluteAccuracy, logDensity, probability, reseedRandomGenerator, sampleprotected final EnumeratedDistribution<Double> innerDistribution
EnumeratedDistribution (using the Double wrapper)
 used to generate the pmf.public EnumeratedRealDistribution(double[] singletons,
                          double[] probabilities)
                           throws DimensionMismatchException,
                                  NotPositiveException,
                                  MathArithmeticException,
                                  NotFiniteNumberException,
                                  NotANumberException
 Note: this constructor will implicitly create an instance of
 Well19937c as random generator to be used for sampling only (see
 sample() and AbstractRealDistribution.sample(int)). In case no sampling is
 needed for the created distribution, it is advised to pass null
 as random generator via the appropriate constructors to avoid the
 additional initialisation overhead.
singletons - array of random variable values.probabilities - array of probabilities.DimensionMismatchException - if
 singletons.length != probabilities.lengthNotPositiveException - if any of the probabilities are negative.NotFiniteNumberException - if any of the probabilities are infinite.NotANumberException - if any of the probabilities are NaN.MathArithmeticException - all of the probabilities are 0.public EnumeratedRealDistribution(RandomGenerator rng, double[] singletons, double[] probabilities) throws DimensionMismatchException, NotPositiveException, MathArithmeticException, NotFiniteNumberException, NotANumberException
rng - random number generator.singletons - array of random variable values.probabilities - array of probabilities.DimensionMismatchException - if
 singletons.length != probabilities.lengthNotPositiveException - if any of the probabilities are negative.NotFiniteNumberException - if any of the probabilities are infinite.NotANumberException - if any of the probabilities are NaN.MathArithmeticException - all of the probabilities are 0.public EnumeratedRealDistribution(RandomGenerator rng, double[] data)
rng - random number generator used for samplingdata - input datasetpublic EnumeratedRealDistribution(double[] data)
data - input datasetpublic double probability(double x)
X whose values are distributed according
 to this distribution, this method returns P(X = x). In other
 words, this method represents the probability mass function (PMF)
 for the distribution.probability in interface RealDistributionprobability in class AbstractRealDistributionx - the point at which the PMF is evaluatedpublic double density(double x)
X whose values are distributed according to
 this distribution, this method returns P(X = x). In other words,
 this method represents the probability mass function (PMF) for the
 distribution.x - the point at which the PMF is evaluatedxpublic double cumulativeProbability(double x)
X whose values are distributed according
 to this distribution, this method returns P(X <= x). In other
 words, this method represents the (cumulative) distribution function
 (CDF) for this distribution.x - the point at which the CDF is evaluatedxpublic double inverseCumulativeProbability(double p)
                                    throws OutOfRangeException
X distributed according to this distribution, the
 returned value is
 inf{x in R | P(X<=x) >= p} for 0 < p <= 1,inf{x in R | P(X<=x) > 0} for p = 0.RealDistribution.getSupportLowerBound() for p = 0,RealDistribution.getSupportUpperBound() for p = 1.inverseCumulativeProbability in interface RealDistributioninverseCumulativeProbability in class AbstractRealDistributionp - the cumulative probabilityp-quantile of this distribution
 (largest 0-quantile for p = 0)OutOfRangeException - if p < 0 or p > 1public double getNumericalMean()
sum(singletons[i] * probabilities[i])public double getNumericalVariance()
sum((singletons[i] - mean) ^ 2 * probabilities[i])public double getSupportLowerBound()
inverseCumulativeProbability(0). In other words, this
 method must return
 inf {x in R | P(X <= x) > 0}.
public double getSupportUpperBound()
inverseCumulativeProbability(1). In other words, this
 method must return
 inf {x in R | P(X <= x) = 1}.
public boolean isSupportLowerBoundInclusive()
getSupporLowerBound() is finite and
 density(getSupportLowerBound()) returns a non-NaN, non-infinite
 value.
 The support of this distribution includes the lower bound.truepublic boolean isSupportUpperBoundInclusive()
getSupportUpperBound() is finite and
 density(getSupportUpperBound()) returns a non-NaN, non-infinite
 value.
 The support of this distribution includes the upper bound.truepublic boolean isSupportConnected()
truepublic double sample()
sample in interface RealDistributionsample in class AbstractRealDistributionCopyright © 2003–2016 The Apache Software Foundation. All rights reserved.