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, Serializable, Product, Equals, VariateMat, Error, AnyRef, Any
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Inherited
  1. RandomMatD
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. VariateMat
  7. Error
  8. AnyRef
  9. Any
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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. val density: Double
  2. val dim1: Int
  3. val dim2: Int
  4. def discrete: Boolean

    Determine whether the distribution is discrete or continuous.

    Determine whether the distribution is discrete or continuous.

    Definition Classes
    VariateMat
  5. 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
  6. 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
    RandomMatDVariateMat
  7. 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
    RandomMatDVariateMat
  8. val max: Double
  9. def mean: MatrixD

    Compute the matrix mean for the particular distribution.

    Compute the matrix mean for the particular distribution.

    Definition Classes
    RandomMatDVariateMat
  10. val min: Double
  11. 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
    RandomMatDVariateMat
  12. 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
    RandomMatDVariateMat
  13. 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
    RandomMatDVariateMat
  14. val stream: Int