Value Members

1.  final def !=(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

2.  final def ##(): Int

   Definition Classes

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3.  final def ==(arg0: Any): Boolean

   Definition Classes

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4.  def _normalCDF(x: Double, pr: Parameters = null): Double

   Compute the Cumulative Distribution Function (CDF) for the Normal distribution.

   Compute the Cumulative Distribution Function (CDF) for the Normal distribution.

   x

   the x coordinate, argument to F(x)

   pr

   parameters for the mean and standard deviation

5.  def _normalCDF(x: Double): Double

   Compute the Cumulative Distribution Function (CDF) 'F(x)' for the Standard Normal distribution using the Hart function.

   Compute the Cumulative Distribution Function (CDF) 'F(x)' for the Standard Normal distribution using the Hart function. Recoded in Scala from C code

   x

   the x coordinate, argument to F(x)

   See also

   www.codeplanet.eu/files/download/accuratecumnorm.pdf

   stackoverflow.com/questions/2328258/cumulative-normal-distribution-function-in-c-c which was recoded from VB code.

6.  final def asInstanceOf[T0]: T0

   Definition Classes

   Any

7.  def buildEmpiricalCDF(x: VectorD): (VectorD, VectorD)

   Build an empirical CDF from input data vector 'x'.

   Build an empirical CDF from input data vector 'x'. Ex: x = (2, 1, 2, 3, 2) -> cdf = ((1, .2), (2, .8), (3, 1.))

   x

   the input data vector

8.  def chiSquareCDF(x: Double, pr: Parameters = null): Double

   Compute the Cumulative Distribution Function (CDF) for the ChiSquare distribution.

   Compute the Cumulative Distribution Function (CDF) for the ChiSquare distribution.

   x

   the x coordinate, argument to F(x)

9.  def chiSquareCDF(x: Double, df: Int): Double

   Compute the Cumulative Distribution Function (CDF) for the ChiSquare distribution by numerically integrating the ChiSquare probability density function (pdf).

   Compute the Cumulative Distribution Function (CDF) for the ChiSquare distribution by numerically integrating the ChiSquare probability density function (pdf). See Variate.scala.

   x

   the x coordinate, argument to F(x)

   df

   the degrees of freedom

10.  def clone(): AnyRef

    Attributes

    protected[java.lang]

    Definition Classes

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    Annotations

    @native() @throws( ... )

11.  def empiricalCDF(x: Double, eCDF: (VectorD, VectorD)): Double

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Empirical distribution 'eCDF'.

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Empirical distribution 'eCDF'.

    x

    the x coordinate, argument to F(x)

    eCDF

    the Empirical CDF

12.  final def eq(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

13.  def equals(arg0: Any): Boolean

    Definition Classes

    AnyRef → Any

14.  def exponentialCDF(x: Double, pr: Parameters = null): Double

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Exponential distribution.

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Exponential distribution.

    x

    the x coordinate, argument to F(x)

15.  def exponentialCDF(x: Double, λ: Double): Double

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Exponential distribution.

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Exponential distribution.

    x

    the x coordinate, argument to F(x)

    λ

    the rate parameter

16.  def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

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

17.  def fisherCDF(x: Double, pr: Parameters = null): Double

    Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.

    Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.

    x

    the x coordinate, argument to F(x)

18.  def fisherCDF(x: Double, df: (Int, Int)): Double

    Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.

    Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.

    x

    the x coordinate, argument to F(x)

    df

    the pair of degrees of freedom ('df1', 'df2')

19.  def fisherCDF(x: Double, df1: Int, df2: Int): Double

    Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.

    Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.

    x

    the x coordinate, argument to F(x)

    df1

    the degrees of freedom 1 (numerator)

    df2

    the degrees of freedom 2 (denominator)

20.  final def flaw(method: String, message: String): Unit

    Show the flaw by printing the error message.

    Show the flaw by printing the error message.

    method

    the method where the error occurred

    message

    the error message

    Definition Classes

    Error

21.  final def getClass(): Class[_]

    Definition Classes

    AnyRef → Any

    Annotations

    @native()

22.  def hashCode(): Int

    Definition Classes

    AnyRef → Any

    Annotations

    @native()

23.  final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

24.  final def ne(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

25.  def noncentralTCDF(x: Double, mu: Double, df: Double): Double

    Compute the Cumulative Distribution Function (CDF) for "Noncentral t" distribution.

    Compute the Cumulative Distribution Function (CDF) for "Noncentral t" distribution.

    x

    the x coordinate, argument to F(x)

    mu

    the noncentrality parameter (or mean)

    df

    the degrees of freedom (must be > 0.0)

    See also

    https://en.wikipedia.org/wiki/Noncentral_t-distribution

26.  def normalCDF(x: Double, pr: Parameters = null): Double

    Compute the Cumulative Distribution Function (CDF) for the Normal distribution.

    Compute the Cumulative Distribution Function (CDF) for the Normal distribution.

    x

    the x coordinate, argument to F(x)

    pr

    parameters for the mean and standard deviation

27.  def normalCDF(x: Double): Double

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Standard Normal distribution using the Hart function.

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Standard Normal distribution using the Hart function. Recoded in Scala from Java code. Apache license given above.

    x

    the x coordinate, argument to F(x)

    See also

    mail-archives.apache.org/mod_mbox/commons-dev/200401.mbox/%3C20040126030431.92035.qmail@minotaur.apache.org%3E

28.  final def notify(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

29.  final def notifyAll(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

30.  def studentTCDF(x: Double, pr: Parameters = null): Double

    Compute the Cumulative Distribution Function (CDF) for "Student's t" distribution.

    Compute the Cumulative Distribution Function (CDF) for "Student's t" distribution.

    x

    the x coordinate, argument to F(x)

    pr

    parameter for the degrees of freedom

31.  def studentTCDF(x: Double, df: Double): Double

    Compute the Cumulative Distribution Function (CDF) for "Student's t" distribution.

    Compute the Cumulative Distribution Function (CDF) for "Student's t" distribution.

    x

    the x coordinate, argument to F(x)

    df

    the degrees of freedom (must be > 0.0)

    See also

    [JKB 1995] Johnson, Kotz & Balakrishnan "Continuous Univariate Distributions" (Volume 2) (2nd Edition) (Chapter 28) (1995)

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

    Definition Classes

    AnyRef

33.  def toString(): String

    Definition Classes

    AnyRef → Any

34.  def uniformCDF(x: Double, pr: Parameters = null): Double

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Uniform distribution.

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Uniform distribution.

    x

    the x coordinate, argument to F(x)

    pr

    parameters giving the end-points of the uniform distribution

35.  def uniformCDF(x: Double, a: Double, b: Double): Double

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Uniform distribution.

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Uniform distribution.

    x

    the x coordinate, argument to F(x)

    a

    the lower end-point of the uniform distribution

    b

    the upper end-point of the uniform distribution

36.  final def wait(): Unit

    Definition Classes

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    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

38.  final def wait(arg0: Long): Unit

    Definition Classes

    AnyRef

    Annotations

    @native() @throws( ... )

39.  def weibullCDF(x: Double, pr: Parameters = null): Double

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Weibull distribution.

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Weibull distribution.

    x

    the x coordinate, argument to F(x)

40.  def weibullCDF(x: Double, α: Double, β: Double): Double

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Weibull distribution.

    Compute the Cumulative Distribution Function 'CDF' 'F(x)' for the Weibull distribution.

    x

    the x coordinate, argument to F(x)

    α

    the shape parameter

    β

    the scale parameter