AbstractRealDistribution
, BetaDistribution
, CauchyDistribution
, ChiSquaredDistribution
, ConstantRealDistribution
, EmpiricalDistribution
, EnumeratedRealDistribution
, ExponentialDistribution
, FDistribution
, GammaDistribution
, GumbelDistribution
, LaplaceDistribution
, LevyDistribution
, LogisticDistribution
, LogNormalDistribution
, NakagamiDistribution
, NormalDistribution
, ParetoDistribution
, TDistribution
, TriangularDistribution
, UniformRealDistribution
, WeibullDistribution
public interface RealDistribution
Modifier and Type | Method | Description |
---|---|---|
double |
cumulativeProbability(double x) |
For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x) . |
double |
density(double x) |
Returns the probability density function (PDF) of this distribution
evaluated at the specified point
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.
|
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 x0,
double x1) |
For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1) . |
double probability(double x0, double x1) throws MathIllegalArgumentException
X
whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1)
.x0
- the exclusive lower boundx1
- the inclusive upper boundx0
and x1
,
excluding the lower and including the upper endpointMathIllegalArgumentException
- if x0 > x1
double density(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.x
- the point at which the PDF is evaluatedx
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
density(double)
.x
- the point at which the PDF is evaluatedx
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 evaluatedx
double inverseCumulativeProbability(double p) throws MathIllegalArgumentException
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
.p
- the cumulative probabilityp
-quantile of this distribution
(largest 0-quantile for p = 0
)MathIllegalArgumentException
- if p < 0
or p > 1
double getNumericalMean()
Double.NaN
if it is not defineddouble getNumericalVariance()
Double.POSITIVE_INFINITY
as
for certain cases in TDistribution
)
or Double.NaN
if it is not defineddouble getSupportLowerBound()
inverseCumulativeProbability(0)
. In other words, this
method must return
inf {x in R | P(X <= x) > 0}
.
Double.NEGATIVE_INFINITY
)double getSupportUpperBound()
inverseCumulativeProbability(1)
. In other words, this
method must return
inf {x in R | P(X <= x) = 1}
.
Double.POSITIVE_INFINITY
)boolean isSupportConnected()
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