scalation.random

Trapezoidal

case class Trapezoidal(a: Double = 0.0, c: Double = 2.0, d: Double = 7.0, b: Double = 10.0, stream: Int = 0) extends Variate with Product with Serializable

This class generates Trapezoidal random variates. This continuous RV models cases where outcomes cluster between two modes. Both Uniform and Triangular are special cases of Trapezoidal.

a

the minimum

c

the first mode

d

the second mode

b

the maximum

stream

the random number stream

See also

http://iopscience.iop.org/0026-1394/44/2/003/pdf/0026-1394_44_2_003.pdf

Linear Supertypes
Serializable, Serializable, Product, Equals, Variate, Error, AnyRef, Any
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  1. Trapezoidal
  2. Serializable
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Instance Constructors

  1. new Trapezoidal(a: Double = 0.0, c: Double = 2.0, d: Double = 7.0, b: Double = 10.0, stream: Int = 0)

    a

    the minimum

    c

    the first mode

    d

    the second mode

    b

    the maximum

    stream

    the random number stream

Value Members

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

    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  4. var _discrete: Boolean

    Indicates whether the distribution is discrete or continuous (default)

    Indicates whether the distribution is discrete or continuous (default)

    Attributes
    protected
    Definition Classes
    Variate
  5. val a: Double

    the minimum

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  7. val b: Double

    the maximum

  8. val c: Double

    the first mode

  9. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. val d: Double

    the second mode

  11. def discrete: Boolean

    Determine whether the distribution is discrete or continuous.

    Determine whether the distribution is discrete or continuous.

    Definition Classes
    Variate
  12. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  13. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  14. 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
  15. def gen: Double

    Determine the next random number for the particular distribution.

    Determine the next random number for the particular distribution.

    Definition Classes
    TrapezoidalVariate
  16. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  17. def igen: Int

    Determine the next random integer for the particular distribution.

    Determine the next random integer for the particular distribution. It is only valid for discrete random variates.

    Definition Classes
    Variate
  18. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  19. val mean: Double

    Pre-compute the mean for the particular distribution.

    Pre-compute the mean for the particular distribution.

    Definition Classes
    TrapezoidalVariate
  20. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  21. final def notify(): Unit

    Definition Classes
    AnyRef
  22. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  23. def pf(z: Double): Double

    Compute the probability function (pf): Either (a) the probability density function (pdf) for continuous RV's or (b) the probability mass function (pmf) for discrete RV's.

    Compute the probability function (pf): Either (a) the probability density function (pdf) for continuous RV's or (b) the probability mass function (pmf) for discrete RV's.

    z

    the mass point whose probability density/mass is sought

    Definition Classes
    TrapezoidalVariate
  24. def pmf(k: Int = 0): Array[Double]

    Return the entire probability mass function (pmf) for finite discrete RV's.

    Return the entire probability mass function (pmf) for finite discrete RV's.

    k

    number of objects of the first type

    Definition Classes
    Variate
  25. val r: Random

    Random number stream selected by the stream number

    Random number stream selected by the stream number

    Attributes
    protected
    Definition Classes
    Variate
  26. val stream: Int

    the random number stream

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

    Definition Classes
    AnyRef
  28. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  30. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Variate

Inherited from Error

Inherited from AnyRef

Inherited from Any

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