Class ChiSquaredDistribution
- java.lang.Object
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- org.hipparchus.distribution.continuous.AbstractRealDistribution
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- org.hipparchus.distribution.continuous.ChiSquaredDistribution
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- All Implemented Interfaces:
Serializable
,RealDistribution
public class ChiSquaredDistribution extends AbstractRealDistribution
Implementation of the chi-squared distribution.
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Field Summary
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Fields inherited from class org.hipparchus.distribution.continuous.AbstractRealDistribution
DEFAULT_SOLVER_ABSOLUTE_ACCURACY
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Constructor Summary
Constructors Constructor Description ChiSquaredDistribution(double degreesOfFreedom)
Create a Chi-Squared distribution with the given degrees of freedom.ChiSquaredDistribution(double degreesOfFreedom, double inverseCumAccuracy)
Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative probability accuracy.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
cumulativeProbability(double x)
For a random variableX
whose values are distributed according to this distribution, this method returnsP(X <= x)
.double
density(double x)
Returns the probability density function (PDF) of this distribution evaluated at the specified pointx
.double
getDegreesOfFreedom()
Access the number of 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.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.double
logDensity(double x)
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified pointx
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Methods inherited from class org.hipparchus.distribution.continuous.AbstractRealDistribution
getSolverAbsoluteAccuracy, inverseCumulativeProbability, probability
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Constructor Detail
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ChiSquaredDistribution
public ChiSquaredDistribution(double degreesOfFreedom)
Create a Chi-Squared distribution with the given degrees of freedom.- Parameters:
degreesOfFreedom
- Degrees of freedom.
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ChiSquaredDistribution
public ChiSquaredDistribution(double degreesOfFreedom, double inverseCumAccuracy)
Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative probability accuracy.- Parameters:
degreesOfFreedom
- Degrees of freedom.inverseCumAccuracy
- the maximum absolute error in inverse cumulative probability estimates (defaults toAbstractRealDistribution.DEFAULT_SOLVER_ABSOLUTE_ACCURACY
).
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Method Detail
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getDegreesOfFreedom
public double getDegreesOfFreedom()
Access the number of degrees of freedom.- Returns:
- the degrees of freedom.
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density
public double density(double x)
Returns the probability density function (PDF) of this distribution evaluated at the specified pointx
. In general, the PDF is the derivative of theCDF
. If the derivative does not exist atx
, 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.- Parameters:
x
- the point at which the PDF is evaluated- Returns:
- the value of the probability density function at point
x
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logDensity
public double logDensity(double x)
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified pointx
. In general, the PDF is the derivative of theCDF
. If the derivative does not exist atx
, 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 ofRealDistribution.density(double)
.The default implementation simply computes the logarithm of
density(x)
.- Specified by:
logDensity
in interfaceRealDistribution
- Overrides:
logDensity
in classAbstractRealDistribution
- Parameters:
x
- the point at which the PDF is evaluated- Returns:
- the logarithm of the value of the probability density function at point
x
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cumulativeProbability
public double cumulativeProbability(double x)
For a random variableX
whose values are distributed according to this distribution, this method returnsP(X <= x)
. In other words, this method represents the (cumulative) distribution function (CDF) for this distribution.- Parameters:
x
- the point at which the CDF is evaluated- Returns:
- the probability that a random variable with this
distribution takes a value less than or equal to
x
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getNumericalMean
public double getNumericalMean()
Use this method to get the numerical value of the mean of this distribution. Fork
degrees of freedom, the mean isk
.- Returns:
- the mean or
Double.NaN
if it is not defined
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getNumericalVariance
public double getNumericalVariance()
Use this method to get the numerical value of the variance of this distribution.- Returns:
2 * k
, wherek
is the number of degrees of freedom.
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getSupportLowerBound
public double getSupportLowerBound()
Access the lower bound of the support. This method must return the same value asinverseCumulativeProbability(0)
. In other words, this method must return
The lower bound of the support is always 0 no matter the degrees of freedom.inf {x in R | P(X <= x) > 0}
.- Returns:
- zero.
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getSupportUpperBound
public double getSupportUpperBound()
Access the upper bound of the support. This method must return the same value asinverseCumulativeProbability(1)
. In other words, this method must return
The upper bound of the support is always positive infinity no matter the degrees of freedom.inf {x in R | P(X <= x) = 1}
.- Returns:
Double.POSITIVE_INFINITY
.
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isSupportConnected
public boolean isSupportConnected()
Use this method to get information about whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support. The support of this distribution is connected.- Returns:
true
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