scalation.random

Normal

case class Normal(mu: Double = 0.0, sigma2: Double = 1.0, stream: Int = 0) extends Variate with Product with Serializable

This class generates Normal (Gaussian) random variates. This continuous RV models normally distributed data (bell curve). When summed, most distributions tend to Normal (Central Limit Theorem).

mu

the mean

sigma2

the variance (sigma squared)

stream

the random number stream

See also

http://www.math.uah.edu/stat/special/Normal.html

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Serializable, Serializable, Product, Equals, Variate, Error, AnyRef, Any
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Instance Constructors

  1. new Normal(mu: Double = 0.0, sigma2: Double = 1.0, stream: Int = 0)

    mu

    the mean

    sigma2

    the variance (sigma squared)

    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. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  6. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  7. def discrete: Boolean

    Determine whether the distribution is discrete or continuous.

    Determine whether the distribution is discrete or continuous.

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

    Definition Classes
    AnyRef
  9. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  10. 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
  11. def gen: Double

    Determine the next random number for the particular distribution.

    Determine the next random number for the particular distribution.

    Definition Classes
    NormalVariate
  12. def gen2: Double

  13. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  14. 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
  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  16. val mean: Double

    Pre-compute the mean for the particular distribution.

    Pre-compute the mean for the particular distribution.

    Definition Classes
    NormalVariate
  17. val mu: Double

    the mean

  18. final def ne(arg0: AnyRef): Boolean

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

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

    Definition Classes
    AnyRef
  21. 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
    NormalVariate
  22. 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
  23. val r: Random

    Random number stream selected by the stream number

    Random number stream selected by the stream number

    Attributes
    protected
    Definition Classes
    Variate
  24. val sigma2: Double

    the variance (sigma squared)

  25. val stream: Int

    the random number stream

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

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. 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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