public class FDistribution extends AbstractRealDistribution
Modifier and Type | Field and Description |
---|---|
static double |
DEFAULT_INVERSE_ABSOLUTE_ACCURACY
Default inverse cumulative probability accuracy.
|
randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY
Constructor and Description |
---|
FDistribution(double numeratorDegreesOfFreedom,
double denominatorDegreesOfFreedom)
Create a F distribution using the given degrees of freedom.
|
FDistribution(double numeratorDegreesOfFreedom,
double denominatorDegreesOfFreedom,
double inverseCumAccuracy)
Create an F distribution using the given degrees of freedom
and inverse cumulative probability accuracy.
|
Modifier and Type | Method and Description |
---|---|
protected double |
calculateNumericalVariance()
used by
getNumericalVariance() |
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 |
getDenominatorDegreesOfFreedom()
Access the denominator degrees of freedom.
|
double |
getNumeratorDegreesOfFreedom()
Access the numerator degrees of freedom.
|
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.
|
protected double |
getSolverAbsoluteAccuracy()
Returns the solver absolute accuracy for inverse cumulative computation.
|
double |
getSupportLowerBound()
Access the lower bound of the support.
|
double |
getSupportUpperBound()
Access the upper bound of the support.
|
boolean |
isSupportConnected()
Use this method to get information about whether the support is connected,
i.e.
|
boolean |
isSupportLowerBoundInclusive()
Use this method to get information about whether the lower bound
of the support is inclusive or not.
|
boolean |
isSupportUpperBoundInclusive()
Use this method to get information about whether the upper bound
of the support is inclusive or not.
|
double |
probability(double x)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(X = x) . |
cumulativeProbability, inverseCumulativeProbability, reseedRandomGenerator, sample, sample
public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
public FDistribution(double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom) throws NotStrictlyPositiveException
numeratorDegreesOfFreedom
- Numerator degrees of freedom.denominatorDegreesOfFreedom
- Denominator degrees of freedom.NotStrictlyPositiveException
- if
numeratorDegreesOfFreedom <= 0
or
denominatorDegreesOfFreedom <= 0
.public FDistribution(double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom, double inverseCumAccuracy) throws NotStrictlyPositiveException
numeratorDegreesOfFreedom
- Numerator degrees of freedom.denominatorDegreesOfFreedom
- Denominator degrees of freedom.inverseCumAccuracy
- the maximum absolute error in inverse
cumulative probability estimates.
(defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY
)NotStrictlyPositiveException
- if
numeratorDegreesOfFreedom <= 0
or
denominatorDegreesOfFreedom <= 0
.public 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.
For this distribution P(X = x)
always evaluates to 0.x
- the point at which the PMF is evaluatedpublic 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
public 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.
The implementation of this method is based on
x
- the point at which the CDF is evaluatedx
public double getNumeratorDegreesOfFreedom()
public double getDenominatorDegreesOfFreedom()
protected double getSolverAbsoluteAccuracy()
getSolverAbsoluteAccuracy
in class AbstractRealDistribution
public double getNumericalMean()
b
, the mean is
b > 2
then b / (b - 2)
,Double.NaN
).
Double.NaN
if it is not definedpublic double getNumericalVariance()
a
and denominator
degrees of freedom parameter b
, the variance is
b > 4
then
[2 * b^2 * (a + b - 2)] / [a * (b - 2)^2 * (b - 4)]
,
Double.NaN
).
Double.POSITIVE_INFINITY
as
for certain cases in TDistribution
) or Double.NaN
if it
is not definedprotected double calculateNumericalVariance()
getNumericalVariance()
public double getSupportLowerBound()
inverseCumulativeProbability(0)
. In other words, this
method must return
inf {x in R | P(X <= x) > 0}
.
public double getSupportUpperBound()
inverseCumulativeProbability(1)
. In other words, this
method must return
inf {x in R | P(X <= x) = 1}
.
public boolean isSupportLowerBoundInclusive()
public boolean isSupportUpperBoundInclusive()
public boolean isSupportConnected()
true
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