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case class Sharp(x: Double = 1, stream: Int = 0) extends Variate with Product with Serializable

This class generates Sharp (Deterministic) random variates. This discrete RV models the case when the variance is 0.

x

the value for this constant distribution

stream

the random number stream

Linear Supertypes
Serializable, Serializable, Product, Equals, Variate, Error, AnyRef, Any
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  1. Sharp
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Variate
  7. Error
  8. AnyRef
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Instance Constructors

  1. new Sharp(x: Double = 1, stream: Int = 0)

    x

    the value for this constant distribution

    stream

    the random number stream

Value Members

  1. def discrete: Boolean

    Determine whether the distribution is discrete or continuous.

    Determine whether the distribution is discrete or continuous.

    Definition Classes
    Variate
  2. 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
  3. def gen: Double

    Determine the next random number for the particular distribution.

    Determine the next random number for the particular distribution.

    Definition Classes
    SharpVariate
  4. def gen1(z: Double): Double

    Determine the next random number for the particular distribution.

    Determine the next random number for the particular distribution. This version allows one parameter.

    z

    the limit parameter

    Definition Classes
    SharpVariate
  5. 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
  6. def igen1(z: Double): 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. This version allows one parameter.

    z

    the limit parameter

    Definition Classes
    Variate
  7. val mean: Double
    Definition Classes
    SharpVariate
  8. 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
    SharpVariate
  9. 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
  10. def sgen: String

    Determine the next random string for the particular distribution.

    Determine the next random string for the particular distribution. For better random strings, overide this method.

    Definition Classes
    Variate
  11. def sgen1(z: Double): String

    Determine the next random string for the particular distribution.

    Determine the next random string for the particular distribution. For better random strings, overide this method. This version allows one parameter.

    z

    the limit parameter

    Definition Classes
    Variate
  12. val stream: Int
  13. val x: Double