public abstract class AbstractIntegerDistribution extends Object implements IntegerDistribution, Serializable
Default implementations are provided for some of the methods that do not vary from distribution to distribution.
| Constructor and Description | 
|---|
| AbstractIntegerDistribution() | 
| Modifier and Type | Method and Description | 
|---|---|
| int | inverseCumulativeProbability(double p)Computes the quantile function of this distribution. | 
| double | logProbability(int x)For a random variable  Xwhose values are distributed according to
 this distribution, this method returnslog(P(X = x)), wherelogis the natural logarithm. | 
| double | probability(int x0,
           int x1)For a random variable  Xwhose values are distributed according
 to this distribution, this method returnsP(x0 < X <= x1). | 
| protected int | solveInverseCumulativeProbability(double p,
                                 int lower,
                                 int upper)This is a utility function used by  inverseCumulativeProbability(double). | 
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitcumulativeProbability, getNumericalMean, getNumericalVariance, getSupportLowerBound, getSupportUpperBound, isSupportConnected, probabilitypublic double probability(int x0,
                          int x1)
                   throws MathIllegalArgumentException
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)
probability in interface IntegerDistributionx0 - the exclusive lower boundx1 - the inclusive upper boundx0 and x1,
 excluding the lower and including the upper endpointMathIllegalArgumentException - if x0 > x1public int inverseCumulativeProbability(double p)
                                 throws MathIllegalArgumentException
X distributed according to this distribution,
 the returned value is
 inf{x in Z | P(X<=x) >= p} for 0 < p <= 1,inf{x in Z | P(X<=x) > 0} for p = 0.int,
 then Integer.MIN_VALUE or Integer.MAX_VALUE is returned.
 The default implementation returns
 IntegerDistribution.getSupportLowerBound() for p = 0,IntegerDistribution.getSupportUpperBound() for p = 1, andsolveInverseCumulativeProbability(double, int, int) for
     0 < p < 1.inverseCumulativeProbability in interface IntegerDistributionp - the cumulative probabilityp-quantile of this distribution
 (largest 0-quantile for p = 0)MathIllegalArgumentException - if p < 0 or p > 1protected int solveInverseCumulativeProbability(double p,
                                                int lower,
                                                int upper)
inverseCumulativeProbability(double). It assumes 0 < p < 1 and
 that the inverse cumulative probability lies in the bracket (lower, upper]. The implementation does simple bisection to find the
 smallest p-quantile inf{x in Z | P(X<=x) >= p}.p - the cumulative probabilitylower - a value satisfying cumulativeProbability(lower) < pupper - a value satisfying p <= cumulativeProbability(upper)p-quantile of this distributionpublic double logProbability(int x)
X whose values are distributed according to
 this distribution, this method returns log(P(X = x)), where
 log is the natural logarithm. In other words, this method
 represents the logarithm of the probability mass function (PMF) for the
 distribution. 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
 IntegerDistribution.probability(int).
 
 The default implementation simply computes the logarithm of probability(x).
logProbability in interface IntegerDistributionx - the point at which the PMF is evaluatedxCopyright © 2016–2020 Hipparchus.org. All rights reserved.