Serializable
, IntegerDistribution
BinomialDistribution
, EnumeratedIntegerDistribution
, GeometricDistribution
, HypergeometricDistribution
, PascalDistribution
, PoissonDistribution
, UniformIntegerDistribution
, ZipfDistribution
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 | Description |
---|---|
AbstractIntegerDistribution() |
Modifier and Type | Method | Description |
---|---|---|
int |
inverseCumulativeProbability(double p) |
Computes the quantile function of this distribution.
|
double |
logProbability(int x) |
For a random variable
X whose values are distributed according to
this distribution, this method returns log(P(X = x)) , where
log is the natural logarithm. |
double |
probability(int x0,
int x1) |
For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1) . |
protected int |
solveInverseCumulativeProbability(double p,
int lower,
int upper) |
This is a utility function used by
inverseCumulativeProbability(double) . |
cumulativeProbability, getNumericalMean, getNumericalVariance, getSupportLowerBound, getSupportUpperBound, isSupportConnected, probability
public 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 IntegerDistribution
x0
- the exclusive lower boundx1
- the inclusive upper boundx0
and x1
,
excluding the lower and including the upper endpointMathIllegalArgumentException
- if x0 > x1
public 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 IntegerDistribution
p
- the cumulative probabilityp
-quantile of this distribution
(largest 0-quantile for p = 0
)MathIllegalArgumentException
- if p < 0
or p > 1
protected 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) < p
upper
- 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 IntegerDistribution
x
- the point at which the PMF is evaluatedx
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