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, samplepublic 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 evaluatedxpublic 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 evaluatedxpublic double getNumeratorDegreesOfFreedom()
public double getDenominatorDegreesOfFreedom()
protected double getSolverAbsoluteAccuracy()
getSolverAbsoluteAccuracy in class AbstractRealDistributionpublic 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()
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