Class EnumeratedRealDistribution

    • Constructor Detail

      • EnumeratedRealDistribution

        public EnumeratedRealDistribution​(double[] data)
        Create a discrete real-valued distribution from the input data. Values are assigned mass based on their frequency. For example, [0,1,1,2] as input creates a distribution with values 0, 1 and 2 having probability masses 0.25, 0.5 and 0.25 respectively,
        Parameters:
        data - input dataset
    • Method Detail

      • probability

        public 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.

        Note that if x1 and x2 satisfy x1.equals(x2), or both are null, then probability(x1) = probability(x2).

        Parameters:
        x - the point at which the PMF is evaluated
        Returns:
        the value of the probability mass function at x
      • density

        public double density​(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
      • 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
      • getNumericalMean

        public double getNumericalMean()
        Use this method to get the numerical value of the mean of this distribution.
        Returns:
        sum(singletons[i] * probabilities[i])
      • getNumericalVariance

        public double getNumericalVariance()
        Use this method to get the numerical value of the variance of this distribution.
        Returns:
        sum((singletons[i] - mean) ^ 2 * probabilities[i])
      • 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}.

        Returns the lowest value with non-zero probability.
        Returns:
        the lowest value with non-zero probability.
      • 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}.

        Returns the highest value with non-zero probability.
        Returns:
        the highest value with non-zero probability.
      • 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
      • getPmf

        public List<Pair<Double,​Double>> getPmf()
        Return the probability mass function as a list of (value, probability) pairs.
        Returns:
        the probability mass function.