DelayedDistribution

Value Members

1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. final def asInstanceOf[T0]: T0

   

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5. def betaDistribution(mu: Double, sigma: Double): Distribution[Double]

   

   continuous probability distributions defined on the interval [0, 1] parametrized by two positive shape parameters, denoted by α and β, that appear as exponents of the random variable and control the shape of the distribution.

   continuous probability distributions defined on the interval [0, 1] parametrized by two positive shape parameters, denoted by α and β, that appear as exponents of the random variable and control the shape of the distribution.

   mu

   mean

   sigma

   stdev

   returns

   Distribution obeying beta: for use scaling should be applied

6. def clone(): AnyRef

   

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   protected[java.lang]

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7. final def eq(arg0: AnyRef): Boolean

   

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8. def equals(arg0: Any): Boolean

   

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9. def finalize(): Unit

   

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   @throws( classOf[java.lang.Throwable] )

10. def future[T](f: Future[T], delay: FiniteDuration)(implicit ec: ExecutionContext, s: Scheduler): Future[T]

    

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    Delay

11. def gammaDistribution(k: Double, theta: Double): Distribution[Double]

    

12. def gammaRatios(p1: Double, x1: Double, p2: Double, x2: Double): (Double, Double)

    

    Function to find roots for gamma distribution parameters

    Function to find roots for gamma distribution parameters

    p1

    probalitity of the first term [0,1]

    x1

    value at that probability

    p2

    probalitity of the second term [0,1]

    x2

    value at that probability

    returns

    The shape and the scale parameter of the gamma distribution that satisfies the given probabilities and values.

13. def gammaRatios(x1: Double, x2: Double): (Double, Double)

    

    Default gamma ratios of 0.5 and 0.9

    Default gamma ratios of 0.5 and 0.9

    x1

    value at probability 50%

    x2

    value at probability 90%

    returns

    The shape and the scale parameter of the gamma distribution that satisfies the given probabilities and values.

14. def getBetaParametersFromMeanAndSigma(mu: Double, sigma: Double): (Double, Double)

    

15. final def getClass(): Class[_]

    

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16. def getWeibullParametersFromPercentiles(p95: Double, p99: Double): (Double, Double)

    
    p95

    the value to satisfy p95

    p99

    the value to satisfy p99

    returns

    the WeibullDistribution

17. final def halveTheIntervalFP(f: (Double) ⇒ Double, x: Double, y: Double, tolerance: Double): Double

    

    Bisection method (Interval Halving method)

    Bisection method (Interval Halving method)

    f

    Function to find root

    x

    left edge

    y

    right edge

    tolerance

    precision

    returns

    The value at which the function's root is.

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    @tailrec()

18. def hashCode(): Int

    

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19. final def isInstanceOf[T0]: Boolean

    

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20. final def ne(arg0: AnyRef): Boolean

    

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21. def normalDistribution(mean: Double, stdev: Double, dist: Distribution[Double]): Distribution[Double]

    

22. final def notify(): Unit

    

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23. final def notifyAll(): Unit

    

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24. def signsAreOpposite(x: Double, y: Double): Boolean

    

    The "signs are opposite" helper function.

25. final def synchronized[T0](arg0: ⇒ T0): T0

    

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26. def toString(): String

    

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27. final def wait(): Unit

    

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28. final def wait(arg0: Long, arg1: Int): Unit

    

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29. final def wait(arg0: Long): Unit

    

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30. def weibullDistribution(p95: Double, p99: Double): Distribution[Double]

    

    Generate weibull distribution