public abstract class AbstractRealDistribution extends Object implements RealDistribution, Serializable
| Modifier and Type | Field and Description | 
|---|---|
| protected RandomGenerator | randomRNG instance used to generate samples from the distribution. | 
| protected RandomDataImpl | randomDataDeprecated. 
 As of 3.1, to be removed in 4.0. Please use the
  randominstance variable instead. | 
| static double | SOLVER_DEFAULT_ABSOLUTE_ACCURACYDefault accuracy. | 
| Modifier | Constructor and Description | 
|---|---|
| protected  | AbstractRealDistribution()Deprecated. 
 As of 3.1, to be removed in 4.0. Please use
  AbstractRealDistribution(RandomGenerator)instead. | 
| protected  | AbstractRealDistribution(RandomGenerator rng) | 
| Modifier and Type | Method and Description | 
|---|---|
| double | cumulativeProbability(double x0,
                     double x1)Deprecated. 
 As of 3.1 (to be removed in 4.0). Please use
  probability(double,double)instead. | 
| protected double | getSolverAbsoluteAccuracy()Returns the solver absolute accuracy for inverse cumulative computation. | 
| double | inverseCumulativeProbability(double p)Computes the quantile function of this distribution. | 
| double | logDensity(double x)Returns the natural logarithm of the probability density function (PDF) of this distribution
 evaluated at the specified point  x. | 
| double | probability(double x)For a random variable  Xwhose values are distributed according
 to this distribution, this method returnsP(X = x). | 
| double | probability(double x0,
           double x1)For a random variable  Xwhose values are distributed according
 to this distribution, this method returnsP(x0 < X <= x1). | 
| void | reseedRandomGenerator(long seed)Reseed the random generator used to generate samples. | 
| double | sample()Generate a random value sampled from this distribution. | 
| double[] | sample(int sampleSize)Generate a random sample from the distribution. | 
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitcumulativeProbability, density, getNumericalMean, getNumericalVariance, getSupportLowerBound, getSupportUpperBound, isSupportConnected, isSupportLowerBoundInclusive, isSupportUpperBoundInclusivepublic static final double SOLVER_DEFAULT_ABSOLUTE_ACCURACY
@Deprecated protected RandomDataImpl randomData
random instance variable instead.protected final RandomGenerator random
@Deprecated protected AbstractRealDistribution()
AbstractRealDistribution(RandomGenerator) instead.protected AbstractRealDistribution(RandomGenerator rng)
rng - Random number generator.@Deprecated public double cumulativeProbability(double x0, double x1) throws NumberIsTooLargeException
probability(double,double) instead.X whose values are distributed according
 to this distribution, this method returns P(x0 < X <= x1).
 The default implementation uses the identity
 P(x0 < X <= x1) = P(X <= x1) - P(X <= x0)
cumulativeProbability in interface RealDistributionx0 - the exclusive lower boundx1 - the inclusive upper boundx0 and x1,
 excluding the lower and including the upper endpointNumberIsTooLargeException - if x0 > x1public double probability(double x0,
                 double x1)
X whose values are distributed according
 to this distribution, this method returns P(x0 < X <= x1).x0 - Lower bound (excluded).x1 - Upper bound (included).x0 and x1, excluding the lower
 and including the upper endpoint.NumberIsTooLargeException - if x0 > x1.
 The default implementation uses the identity
 P(x0 < X <= x1) = P(X <= x1) - P(X <= x0)public 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 RealDistributionp - the cumulative probabilityp-quantile of this distribution
 (largest 0-quantile for p = 0)OutOfRangeException - if p < 0 or p > 1protected double getSolverAbsoluteAccuracy()
public void reseedRandomGenerator(long seed)
reseedRandomGenerator in interface RealDistributionseed - the new seedpublic double sample()
sample in interface RealDistributionpublic double[] sample(int sampleSize)
sample() in a loop.sample in interface RealDistributionsampleSize - the number of random values to generatepublic 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 RealDistributionx - the point at which the PMF is evaluatedpublic double logDensity(double x)
x. In general, the PDF is the derivative of the
 CDF. If the derivative does not exist at x,
 then an appropriate replacement should be returned, e.g. Double.POSITIVE_INFINITY,
 Double.NaN, or the limit inferior or limit superior of the difference quotient. Note
 that due to the floating point precision and under/overflow issues, this method will for some
 distributions be more precise and faster than computing the logarithm of
 RealDistribution.density(double). The default implementation simply computes the logarithm of
 density(x).x - the point at which the PDF is evaluatedxCopyright © 2003–2016 The Apache Software Foundation. All rights reserved.