public interface RealDistribution
| Modifier and Type | Method and 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 |
cumulativeProbability(double x0,
double x1)
Deprecated.
As of 3.1. In 4.0, this method will be renamed
probability(double x0, double x1). |
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.
|
boolean |
isSupportLowerBoundInclusive()
Deprecated.
to be removed in 4.0
|
boolean |
isSupportUpperBoundInclusive()
Deprecated.
to be removed in 4.0
|
double |
probability(double x)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(X = x). |
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.
|
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.x - the point at which the PMF is evaluatedxdouble 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 evaluatedxdouble 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@Deprecated double cumulativeProbability(double x0, double x1) throws NumberIsTooLargeException
probability(double x0, double x1).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 endpointNumberIsTooLargeException - if x0 > x1double 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.p - the cumulative probabilityp-quantile of this distribution
(largest 0-quantile for p = 0)OutOfRangeException - if p < 0 or p > 1double 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)@Deprecated boolean isSupportLowerBoundInclusive()
getSupporLowerBound() is finite and
density(getSupportLowerBound()) returns a non-NaN, non-infinite
value.@Deprecated boolean isSupportUpperBoundInclusive()
getSupportUpperBound() is finite and
density(getSupportUpperBound()) returns a non-NaN, non-infinite
value.boolean isSupportConnected()
void reseedRandomGenerator(long seed)
seed - the new seeddouble sample()
double[] sample(int sampleSize)
sampleSize - the number of random values to generateNotStrictlyPositiveException - if sampleSize is not positiveCopyright © 2003–2016 The Apache Software Foundation. All rights reserved.