Method Detail

• probability

  double probability(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 probability mass function (PMF) for the distribution.

  Parameters:

  x - the point at which the PMF is evaluated

  Returns:

  the value of the probability mass function at point x

• probability

  double probability(double x0,
                   double x1)
                     throws NumberIsTooLargeException

  For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).

  Parameters:

  x0 - the exclusive lower bound

  x1 - the inclusive upper bound

  Returns:

  the probability that a random variable with this distribution takes a value between x0 and x1, excluding the lower and including the upper endpoint

  Throws:

  NumberIsTooLargeException - if x0 > x1

  Since:

  4.0, was previously named cumulativeProbability

• density

  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

• logDensity

  double logDensity(double x)

  Returns the natural logarithm of 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. 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 density(double).

  Parameters:

  x - the point at which the PDF is evaluated

  Returns:

  the logarithm of the value of the probability density function at point x

  Since:

  4.0

• cumulativeProbability

  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

• inverseCumulativeProbability

  double inverseCumulativeProbability(double p)
                                      throws OutOfRangeException

  Computes the quantile function of this distribution. For a random variable X distributed according to this distribution, the returned value is

  • inf{x in R | P(X<=x) >= p} for 0 < p <= 1,
  • inf{x in R | P(X<=x) > 0} for p = 0.

  Parameters:

  p - the cumulative probability

  Returns:

  the smallest p-quantile of this distribution (largest 0-quantile for p = 0)

  Throws:

  OutOfRangeException - if p < 0 or p > 1

• getNumericalMean

  double getNumericalMean()

  Use this method to get the numerical value of the mean of this distribution.

  Returns:

  the mean or Double.NaN if it is not defined

• getNumericalVariance

  double getNumericalVariance()

  Use this method to get the numerical value of the variance of this distribution.

  Returns:

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

• getSupportLowerBound

  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}.

  Returns:

  lower bound of the support (might be Double.NEGATIVE_INFINITY)

• getSupportUpperBound

  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}.

  Returns:

  upper bound of the support (might be Double.POSITIVE_INFINITY)

• isSupportConnected

  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.

  Returns:

  whether the support is connected or not

• reseedRandomGenerator

  void reseedRandomGenerator(long seed)

  Reseed the random generator used to generate samples.

  Parameters:

  seed - the new seed

• sample

  double sample()

  Generate a random value sampled from this distribution.

  Returns:

  a random value.

• sample

  double[] sample(int sampleSize)

  Generate a random sample from the distribution.

  Parameters:

  sampleSize - the number of random values to generate

  Returns:

  an array representing the random sample

  Throws:

  NotStrictlyPositiveException - if sampleSize is not positive