public class TDistribution extends AbstractRealDistribution
| Modifier and Type | Field and Description | 
|---|---|
| static double | DEFAULT_INVERSE_ABSOLUTE_ACCURACYDefault inverse cumulative probability accuracy. | 
random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY| Constructor and Description | 
|---|
| TDistribution(double degreesOfFreedom)Create a t distribution using the given degrees of freedom. | 
| TDistribution(double degreesOfFreedom,
             double inverseCumAccuracy)Create a t distribution using the given degrees of freedom and the
 specified inverse cumulative probability absolute accuracy. | 
| TDistribution(RandomGenerator rng,
             double degreesOfFreedom)Creates a t distribution. | 
| TDistribution(RandomGenerator rng,
             double degreesOfFreedom,
             double inverseCumAccuracy)Creates a t distribution. | 
| Modifier and Type | Method and Description | 
|---|---|
| double | cumulativeProbability(double x)For a random variable  Xwhose 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 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. | 
| boolean | isSupportLowerBoundInclusive()Whether or not the lower bound of support is in the domain of the density
 function. | 
| boolean | isSupportUpperBoundInclusive()Whether or not the upper bound of support is in the domain of the density
 function. | 
| double | logDensity(double x)Returns the natural logarithm of the probability density function (PDF) of this distribution
 evaluated at the specified point  x. | 
cumulativeProbability, inverseCumulativeProbability, probability, probability, reseedRandomGenerator, sample, samplepublic static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
public TDistribution(double degreesOfFreedom)
              throws NotStrictlyPositiveException
 Note: this constructor will implicitly create an instance of
 Well19937c as random generator to be used for sampling only (see
 AbstractRealDistribution.sample() and AbstractRealDistribution.sample(int)). In case no sampling is
 needed for the created distribution, it is advised to pass null
 as random generator via the appropriate constructors to avoid the
 additional initialisation overhead.
degreesOfFreedom - Degrees of freedom.NotStrictlyPositiveException - if degreesOfFreedom <= 0public TDistribution(double degreesOfFreedom,
             double inverseCumAccuracy)
              throws NotStrictlyPositiveException
 Note: this constructor will implicitly create an instance of
 Well19937c as random generator to be used for sampling only (see
 AbstractRealDistribution.sample() and AbstractRealDistribution.sample(int)). In case no sampling is
 needed for the created distribution, it is advised to pass null
 as random generator via the appropriate constructors to avoid the
 additional initialisation overhead.
degreesOfFreedom - Degrees of freedom.inverseCumAccuracy - the maximum absolute error in inverse
 cumulative probability estimates
 (defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY).NotStrictlyPositiveException - if degreesOfFreedom <= 0public TDistribution(RandomGenerator rng, double degreesOfFreedom) throws NotStrictlyPositiveException
rng - Random number generator.degreesOfFreedom - Degrees of freedom.NotStrictlyPositiveException - if degreesOfFreedom <= 0public TDistribution(RandomGenerator rng, double degreesOfFreedom, double inverseCumAccuracy) throws NotStrictlyPositiveException
rng - Random number generator.degreesOfFreedom - Degrees of freedom.inverseCumAccuracy - the maximum absolute error in inverse
 cumulative probability estimates
 (defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY).NotStrictlyPositiveException - if degreesOfFreedom <= 0public double getDegreesOfFreedom()
public 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 logDensity(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. 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 of
 RealDistribution.density(double). The default implementation simply computes the logarithm of
 density(x).logDensity in class AbstractRealDistributionx - 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.x - the point at which the CDF is evaluatedxprotected double getSolverAbsoluteAccuracy()
getSolverAbsoluteAccuracy in class AbstractRealDistributionpublic double getNumericalMean()
df, the mean is
 df > 1 then 0,Double.NaN).Double.NaN if it is not definedpublic double getNumericalVariance()
df, the variance is
 df > 2 then df / (df - 2),1 < df <= 2 then positive infinity
  (Double.POSITIVE_INFINITY),Double.NaN).Double.POSITIVE_INFINITY as
 for certain cases in TDistribution) or Double.NaN if it
 is not definedpublic double getSupportLowerBound()
inverseCumulativeProbability(0). In other words, this
 method must return
 inf {x in R | P(X <= x) > 0}.
Double.NEGATIVE_INFINITY)public double getSupportUpperBound()
inverseCumulativeProbability(1). In other words, this
 method must return
 inf {x in R | P(X <= x) = 1}.
Double.POSITIVE_INFINITY)public boolean isSupportLowerBoundInclusive()
getSupporLowerBound() is finite and
 density(getSupportLowerBound()) returns a non-NaN, non-infinite
 value.public boolean isSupportUpperBoundInclusive()
getSupportUpperBound() is finite and
 density(getSupportUpperBound()) returns a non-NaN, non-infinite
 value.public boolean isSupportConnected()
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