Class FoldedNormalDistribution.RegularFoldedNormalDistribution

    • Field Detail

      • mu

        private final double mu
        The location.
      • mean

        private final double mean
        Cached value for inverse probability function.
      • variance

        private final double variance
        Cached value for inverse probability function.
    • Constructor Detail

      • RegularFoldedNormalDistribution

        RegularFoldedNormalDistribution​(double mu,
                                        double sigma)
        Parameters:
        mu - Location parameter.
        sigma - Scale parameter.
    • Method Detail

      • density

        public double density​(double x)
        Description copied from interface: ContinuousDistribution
        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 - Point at which the PDF is evaluated.
        Returns:
        the value of the probability density function at x.
      • probability

        public double probability​(double x0,
                                  double x1)
        Description copied from class: AbstractContinuousDistribution
        For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1). The default implementation uses the identity P(x0 < X <= x1) = P(X <= x1) - P(X <= x0)
        Specified by:
        probability in interface ContinuousDistribution
        Overrides:
        probability in class AbstractContinuousDistribution
        Parameters:
        x0 - Lower bound (exclusive).
        x1 - Upper bound (inclusive).
        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.
      • cumulativeProbability

        public double cumulativeProbability​(double x)
        Description copied from interface: ContinuousDistribution
        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 - 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.
      • survivalProbability

        public double survivalProbability​(double x)
        Description copied from interface: ContinuousDistribution
        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 complementary cumulative distribution function.

        By default, this is defined as 1 - cumulativeProbability(x), but the specific implementation may be more accurate.

        Parameters:
        x - Point at which the survival function is evaluated.
        Returns:
        the probability that a random variable with this distribution takes a value greater than x.
      • getMean

        public double getMean()
        Description copied from class: FoldedNormalDistribution
        Gets the mean of this distribution.

        For location parameter \( \mu \) and scale parameter \( \sigma \), the mean is:

        \[ \sigma \sqrt{ \frac 2 \pi } \exp \left( \frac{-\mu^2}{2\sigma^2} \right) + \mu \operatorname{erf} \left( \frac \mu {\sqrt{2\sigma^2}} \right) \]

        where \( \operatorname{erf} \) is the error function.

        Specified by:
        getMean in interface ContinuousDistribution
        Specified by:
        getMean in class FoldedNormalDistribution
        Returns:
        the mean.