Packages

c

scalation.random

RandomMatD

case class RandomMatD(dim1: Int = 5, dim2: Int = 10, max: Double = 20.0, min: Double = 0.0, density: Double = 1.0, stream: Int = 0) extends VariateMat with Product with Serializable

The RandomMatD class generates a random matrix of doubles.

dim1

the number of rows in the matrix

dim2

the number of columns in the matrix

max

generate integers in the range 0 (inclusive) to max (inclusive)

min

generate integers in the range 0 (inclusive) to max (inclusive)

density

sparsity basis = 1 - density

stream

the random number stream

Linear Supertypes
Serializable, Product, Equals, VariateMat, Error, AnyRef, Any
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Inherited
  1. RandomMatD
  2. Serializable
  3. Product
  4. Equals
  5. VariateMat
  6. Error
  7. AnyRef
  8. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new RandomMatD(dim1: Int = 5, dim2: Int = 10, max: Double = 20.0, min: Double = 0.0, density: Double = 1.0, stream: Int = 0)

    dim1

    the number of rows in the matrix

    dim2

    the number of columns in the matrix

    max

    generate integers in the range 0 (inclusive) to max (inclusive)

    min

    generate integers in the range 0 (inclusive) to max (inclusive)

    density

    sparsity basis = 1 - density

    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
    VariateMat
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
  7. val density: Double
  8. val dim1: Int
  9. val dim2: Int
  10. def discrete: Boolean

    Determine whether the distribution is discrete or continuous.

    Determine whether the distribution is discrete or continuous.

    Definition Classes
    VariateMat
  11. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  12. final def flaw(method: String, message: String): Unit
    Definition Classes
    Error
  13. def gen: MatrixD

    Determine the next random double matrix for the particular distribution.

    Determine the next random double matrix for the particular distribution.

    Definition Classes
    RandomMatD → VariateMat
  14. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  15. def igen: MatrixI

    Determine the next random integer matrix for the particular distribution.

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

    Definition Classes
    RandomMatD → VariateMat
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. val max: Double
  18. def mean: MatrixD

    Compute the matrix mean for the particular distribution.

    Compute the matrix mean for the particular distribution.

    Definition Classes
    RandomMatD → VariateMat
  19. val min: Double
  20. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  21. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  22. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  23. def pf(z: MatrixD): Double

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

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

    z

    the mass point/matrix whose probability is sought

    Definition Classes
    RandomMatD → VariateMat
  24. def productElementNames: Iterator[String]
    Definition Classes
    Product
  25. val r: Random

    Random number stream selected by the stream number

    Random number stream selected by the stream number

    Attributes
    protected
    Definition Classes
    VariateMat
  26. def rlegenc: RleMatrixD

    Determine the next random Rle matrix for the particular distribution.

    Determine the next random Rle matrix for the particular distribution. Repetition based upon runLength is used to create column vectors.

    Definition Classes
    RandomMatD → VariateMat
  27. def rlegenr: RleMatrixD

    Determine the next random Rle matrix for the particular distribution.

    Determine the next random Rle matrix for the particular distribution. Repetition based upon runLength is used to create row vectors.

    Definition Classes
    RandomMatD → VariateMat
  28. val stream: Int
  29. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  30. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  31. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  32. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable]) @Deprecated
    Deprecated

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from VariateMat

Inherited from Error

Inherited from AnyRef

Inherited from Any

Ungrouped