Module ojalgo
Package org.ojalgo.random

Class Uniform

    • Field Detail

      • myLower

        private final double myLower

      • myRange

        private final double myRange

    • Constructor Detail

      • Uniform

        public Uniform()

      • Uniform

        public Uniform​(double lower,
               double range)

    • Method Detail

      • of

        public static Uniform of​(double lower,
                         double range)

      • randomInteger

        public static int randomInteger​(int limit)
        Returns:
        An integer: 0 <= ? < limit

      • randomInteger

        public static int randomInteger​(int lower,
                                int higher)
        Returns:
        An integer: lower <= ? < higher

      • randomInteger

        public static long randomInteger​(long limit)
        Returns:
        An integer: 0 <= ? < limit

      • standard

        public static Uniform standard()

      • getDensity

        public double getDensity​(double value)
        Description copied from interface: ContinuousDistribution
        In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point. The probability for the random variable to fall within a particular region is given by the integral of this variable's density over the region. The probability density function is nonnegative everywhere, and its integral over the entire space is equal to one. WikipediA
        Parameters:
        value - x
        Returns:
        P(x)

      • getDistribution

        public double getDistribution​(double value)
        Description copied from interface: ContinuousDistribution
        In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable X with a given probability distribution will be found at a value less than or equal to x. Intuitively, it is the "area so far" function of the probability distribution. Cumulative distribution functions are also used to specify the distribution of multivariate random variables. WikipediA
        Parameters:
        value - x
        Returns:
        P(≤x)

      • getExpected

        public double getExpected()

      • getQuantile

        public double getQuantile​(double probability)
        Description copied from interface: ContinuousDistribution
        The quantile function, for any distribution, is defined for real variables between zero and one and is mathematically the inverse of the cumulative distribution function. WikipediA The input probability absolutely has to be [0.0, 1.0], but values close to 0.0 and 1.0 may be problematic
        Parameters:
        probability - P(<=x)
        Returns:
        x