public class ChiSquaredDistributionImpl extends AbstractContinuousDistribution implements ChiSquaredDistribution, java.io.Serializable
ChiSquaredDistribution| Modifier and Type | Field and Description |
|---|---|
static double |
DEFAULT_INVERSE_ABSOLUTE_ACCURACY
Default inverse cumulative probability accuracy
|
private GammaDistribution |
gamma
Internal Gamma distribution.
|
private static long |
serialVersionUID
Serializable version identifier
|
private double |
solverAbsoluteAccuracy
Inverse cumulative probability accuracy
|
randomData| Constructor and Description |
|---|
ChiSquaredDistributionImpl(double df)
Create a Chi-Squared distribution with the given degrees of freedom.
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ChiSquaredDistributionImpl(double df,
double inverseCumAccuracy)
Create a Chi-Squared distribution with the given degrees of freedom and
inverse cumulative probability accuracy.
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ChiSquaredDistributionImpl(double df,
GammaDistribution g)
Deprecated.
as of 2.1 (to avoid possibly inconsistent state, the
"GammaDistribution" will be instantiated internally)
|
| Modifier and Type | Method and Description |
|---|---|
double |
cumulativeProbability(double x)
For this distribution, X, this method returns P(X < x).
|
double |
density(double x)
Return the probability density for a particular point.
|
double |
density(java.lang.Double x)
Deprecated.
|
double |
getDegreesOfFreedom()
Access the degrees of freedom.
|
protected double |
getDomainLowerBound(double p)
Access the domain value lower bound, based on
p, used to
bracket a CDF root. |
protected double |
getDomainUpperBound(double p)
Access the domain value upper bound, based on
p, used to
bracket a CDF root. |
protected double |
getInitialDomain(double p)
Access the initial domain value, based on
p, used to
bracket a CDF root. |
double |
getNumericalMean()
Returns the mean of the distribution.
|
double |
getNumericalVariance()
Returns the variance of the distribution.
|
protected double |
getSolverAbsoluteAccuracy()
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
|
double |
getSupportLowerBound()
Returns the lower bound of the support for the distribution.
|
double |
getSupportUpperBound()
Returns the upper bound for the support for the distribution.
|
double |
inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such
that P(X < x) =
p. |
void |
setDegreesOfFreedom(double degreesOfFreedom)
Deprecated.
as of 2.1 (class will become immutable in 3.0)
|
private void |
setDegreesOfFreedomInternal(double degreesOfFreedom)
Modify the degrees of freedom.
|
void |
setGamma(GammaDistribution g)
Deprecated.
as of 2.1 (class will become immutable in 3.0)
|
private void |
setGammaInternal(GammaDistribution g)
Modify the underlying gamma distribution.
|
reseedRandomGenerator, sample, samplecumulativeProbabilityclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitcumulativeProbabilitypublic static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
private static final long serialVersionUID
private GammaDistribution gamma
private final double solverAbsoluteAccuracy
public ChiSquaredDistributionImpl(double df)
df - degrees of freedom.@Deprecated
public ChiSquaredDistributionImpl(double df,
GammaDistribution g)
df - degrees of freedom.g - the underlying gamma distribution used to compute probabilities.public ChiSquaredDistributionImpl(double df,
double inverseCumAccuracy)
df - degrees of freedom.inverseCumAccuracy - the maximum absolute error in inverse cumulative probability estimates
(defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY)@Deprecated public void setDegreesOfFreedom(double degreesOfFreedom)
setDegreesOfFreedom in interface ChiSquaredDistributiondegreesOfFreedom - the new degrees of freedom.private void setDegreesOfFreedomInternal(double degreesOfFreedom)
degreesOfFreedom - the new degrees of freedom.public double getDegreesOfFreedom()
getDegreesOfFreedom in interface ChiSquaredDistribution@Deprecated public double density(java.lang.Double x)
density in interface ChiSquaredDistributiondensity in interface HasDensity<java.lang.Double>x - The point at which the density should be computed.public double density(double x)
density in class AbstractContinuousDistributionx - The point at which the density should be computed.public double cumulativeProbability(double x)
throws MathException
cumulativeProbability in interface Distributionx - the value at which the CDF is evaluated.MathException - if the cumulative probability can not be
computed due to convergence or other numerical errors.public double inverseCumulativeProbability(double p)
throws MathException
p.
Returns 0 for p=0 and Double.POSITIVE_INFINITY for p=1.
inverseCumulativeProbability in interface ContinuousDistributioninverseCumulativeProbability in class AbstractContinuousDistributionp - the desired probabilitypMathException - if the inverse cumulative probability can not be
computed due to convergence or other numerical errors.java.lang.IllegalArgumentException - if p is not a valid
probability.protected double getDomainLowerBound(double p)
p, used to
bracket a CDF root. This method is used by
inverseCumulativeProbability(double) to find critical values.getDomainLowerBound in class AbstractContinuousDistributionp - the desired probability for the critical valuepprotected double getDomainUpperBound(double p)
p, used to
bracket a CDF root. This method is used by
inverseCumulativeProbability(double) to find critical values.getDomainUpperBound in class AbstractContinuousDistributionp - the desired probability for the critical valuepprotected double getInitialDomain(double p)
p, used to
bracket a CDF root. This method is used by
inverseCumulativeProbability(double) to find critical values.getInitialDomain in class AbstractContinuousDistributionp - the desired probability for the critical value@Deprecated public void setGamma(GammaDistribution g)
g - the new distribution.private void setGammaInternal(GammaDistribution g)
g - the new distribution.protected double getSolverAbsoluteAccuracy()
getSolverAbsoluteAccuracy in class AbstractContinuousDistributionpublic double getSupportLowerBound()
public double getSupportUpperBound()
public double getNumericalMean()
k degrees of freedom, the mean is
kpublic double getNumericalVariance()
k degrees of freedom, the variance is
2 * kCopyright (c) 2003-2013 Apache Software Foundation