fr.cnes.sirius.patrius.math.distribution

Class TDistribution

java.lang.Object

fr.cnes.sirius.patrius.math.distribution.AbstractRealDistribution

fr.cnes.sirius.patrius.math.distribution.TDistribution

All Implemented Interfaces:

RealDistribution, Serializable

public class TDistribution
extends AbstractRealDistribution

Implementation of Student's t-distribution.

Version:

$Id: TDistribution.java 18108 2017-10-04 06:45:27Z bignon $

See Also:

"Student's t-distribution (Wikipedia)", "Student's t-distribution (MathWorld)", Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_INVERSE_ABSOLUTE_ACCURACY Default inverse cumulative probability accuracy.

Fields inherited from class fr.cnes.sirius.patrius.math.distribution.AbstractRealDistribution

random, SOLVER_DEFAULT_ABSOLUTE_ACCURACY

Constructor Summary

Constructors

Constructor and Description
TDistribution(double degreesOfFreedomIn) Create a t distribution using the given degrees of freedom.
TDistribution(double degreesOfFreedomIn, double inverseCumAccuracy) Create a t distribution using the given degrees of freedom and the specified inverse cumulative probability absolute accuracy.
TDistribution(RandomGenerator rng, double degreesOfFreedomIn, double inverseCumAccuracy) Creates a t distribution.

Method Summary

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	density(double x) Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
double	getDegreesOfFreedom() Access the 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. whether all values between the lower and upper bound of the support are included in the support.
boolean	isSupportLowerBoundInclusive() Returns true if support contains lower bound.
boolean	isSupportUpperBoundInclusive() Returns true if support contains upper bound.

Methods inherited from class fr.cnes.sirius.patrius.math.distribution.AbstractRealDistribution

inverseCumulativeProbability, probability, probability, reseedRandomGenerator, sample, sample

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

DEFAULT_INVERSE_ABSOLUTE_ACCURACY

public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY

Default inverse cumulative probability accuracy.

Since:

2.1

See Also:

Constant Field Values

Constructor Detail

TDistribution

public TDistribution(double degreesOfFreedomIn)

Create a t distribution using the given degrees of freedom.

Parameters:

degreesOfFreedomIn - Degrees of freedom.

Throws:

NotStrictlyPositiveException - if degreesOfFreedom <= 0

TDistribution

public TDistribution(double degreesOfFreedomIn,
                     double inverseCumAccuracy)

Create a t distribution using the given degrees of freedom and the specified inverse cumulative probability absolute accuracy.

Parameters:

degreesOfFreedomIn - Degrees of freedom.

inverseCumAccuracy - the maximum absolute error in inverse cumulative probability estimates (defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY).

Throws:

NotStrictlyPositiveException - if degreesOfFreedom <= 0

Since:

2.1

TDistribution

public TDistribution(RandomGenerator rng,
                     double degreesOfFreedomIn,
                     double inverseCumAccuracy)

Creates a t distribution.

Parameters:

rng - Random number generator.

degreesOfFreedomIn - Degrees of freedom.

inverseCumAccuracy - the maximum absolute error in inverse cumulative probability estimates (defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY).

Throws:

NotStrictlyPositiveException - if degreesOfFreedom <= 0

Since:

3.1

Method Detail

getDegreesOfFreedom

public double getDegreesOfFreedom()

Access the degrees of freedom.

Returns:

the degrees of freedom.

density

public double density(double x)

Returns the probability density function (PDF) of this distribution evaluated at the specified point 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.

Parameters:

x - the point at which the PDF is evaluated

Returns:

the value of the probability density function at point x

cumulativeProbability

public double cumulativeProbability(double x)

For a random variable 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.

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

getSolverAbsoluteAccuracy

protected double getSolverAbsoluteAccuracy()

Returns the solver absolute accuracy for inverse cumulative computation. You can override this method in order to use a Brent solver with an absolute accuracy different from the default.

Overrides:

getSolverAbsoluteAccuracy in class AbstractRealDistribution

Returns:

the maximum absolute error in inverse cumulative probability estimates

getNumericalMean

public double getNumericalMean()

Use this method to get the numerical value of the mean of this distribution. For degrees of freedom parameter df, the mean is

• if df > 1 then 0,
• else undefined (Double.NaN).

Returns:

the mean or Double.NaN if it is not defined

getNumericalVariance

public double getNumericalVariance()

Use this method to get the numerical value of the variance of this distribution. For degrees of freedom parameter df, the variance is

• if df > 2 then df / (df - 2),
• if 1 < df <= 2 then positive infinity (Double.POSITIVE_INFINITY),
• else undefined (Double.NaN).

Returns:

the variance (possibly Double.POSITIVE_INFINITY as for certain cases in TDistribution) or Double.NaN if it is not defined

getSupportLowerBound

public double getSupportLowerBound()

Access the lower bound of the support. This method must return the same value as inverseCumulativeProbability(0). In other words, this method must return

inf {x in R | P(X <= x) > 0}.

The lower bound of the support is always negative infinity no matter the parameters.

Returns:

lower bound of the support (always Double.NEGATIVE_INFINITY)

getSupportUpperBound

public double getSupportUpperBound()

Access the upper bound of the support. This method must return the same value as inverseCumulativeProbability(1). In other words, this method must return

inf {x in R | P(X <= x) = 1}.

The upper bound of the support is always positive infinity no matter the parameters.

Returns:

upper bound of the support (always Double.POSITIVE_INFINITY)

isSupportLowerBoundInclusive

public boolean isSupportLowerBoundInclusive()

Returns true if support contains lower bound.

Returns:

false

isSupportUpperBoundInclusive

public boolean isSupportUpperBoundInclusive()

Returns true if support contains upper bound.

Returns:

false

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