Packages

c

scalation.random

RandomVecI

case class RandomVecI(dim: Int = 10, max: Int = 20, min: Int = 10, skip: Int = -1, unique: Boolean = true, stream: Int = 0) extends VariateVec with Product with Serializable

The RandomVecI class generates a random vector of integers. Ex: (3, 2, 0, 4, 1) has 'dim' = 5 and 'max' = 4.

dim

the dimension/size of the vector (number of elements)

max

generate integers in the range min (inclusive) to max (inclusive)

min

generate integers in the range min (inclusive) to max (inclusive)

skip

skip this number, i.e, do not use it

unique

whether the integers must be unique

stream

the random number stream

Linear Supertypes
Serializable, Serializable, Product, Equals, VariateVec, Error, AnyRef, Any
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Inherited
  1. RandomVecI
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. VariateVec
  7. Error
  8. AnyRef
  9. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new RandomVecI(dim: Int = 10, max: Int = 20, min: Int = 10, skip: Int = -1, unique: Boolean = true, stream: Int = 0)

    dim

    the dimension/size of the vector (number of elements)

    max

    generate integers in the range min (inclusive) to max (inclusive)

    min

    generate integers in the range min (inclusive) to max (inclusive)

    skip

    skip this number, i.e, do not use it

    unique

    whether the integers must be unique

    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
    VariateVec
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  7. val dim: Int
  8. def discrete: Boolean

    Determine whether the distribution is discrete or continuous.

    Determine whether the distribution is discrete or continuous.

    Definition Classes
    VariateVec
  9. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  10. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. 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
  12. def gen: VectoD

    Determine the next random double vector for the particular distribution.

    Determine the next random double vector for the particular distribution.

    Definition Classes
    RandomVecIVariateVec
  13. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  14. def igen: VectoI

    Determine the next random integer vector for the particular distribution.

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

    Definition Classes
    RandomVecIVariateVec
  15. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  16. val max: Int
  17. def mean: VectoD

    Compute the vector mean for the particular distribution.

    Compute the vector mean for the particular distribution.

    Definition Classes
    RandomVecIVariateVec
  18. val min: Int
  19. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  20. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  21. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  22. def pf(z: VectoD): Double

    Compute the probability function (pf): The probability density function (pdf) for continuous RVV's or the probability mass function (pmf) for discrete RVV's.

    Compute the probability function (pf): The probability density function (pdf) for continuous RVV's or the probability mass function (pmf) for discrete RVV's.

    z

    the mass point/vector whose probability is sought

    Definition Classes
    RandomVecIVariateVec
  23. val r: Random

    Random number stream selected by the stream number

    Random number stream selected by the stream number

    Attributes
    protected
    Definition Classes
    VariateVec
  24. val skip: Int
  25. val stream: Int
  26. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  27. val unique: Boolean
  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
    @native() @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from VariateVec

Inherited from Error

Inherited from AnyRef

Inherited from Any

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