scalation.random

Normal

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

This class generates Normal (Gaussian) random variates. This continuous RV models normally distributed data.

mu

the mean

sigma2

the variance (sigma squared)

stream

the random number stream

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

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: AnyRef): Boolean

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. 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
  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  8. def canEqual(arg0: Any): Boolean

    Definition Classes
    Normal → Equals
  9. def clone(): AnyRef

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

    Determine whether the distribution is discrete or continuous.

    Determine whether the distribution is discrete or continuous.

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

    Definition Classes
    AnyRef
  12. def equals(arg0: Any): Boolean

    Definition Classes
    Normal → Equals → AnyRef → Any
  13. def finalize(): Unit

    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()
  14. 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
  15. def gen: Double

    Determine the next random number for the particular distribution.

    Determine the next random number for the particular distribution.

    Definition Classes
    NormalVariate
  16. def gen2: Double

  17. final def getClass(): java.lang.Class[_]

    Definition Classes
    AnyRef → Any
  18. def hashCode(): Int

    Definition Classes
    Normal → AnyRef → Any
  19. 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
  20. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  21. def mean: Double

    Compute the mean for the particular distribution.

    Compute the mean for the particular distribution.

    Definition Classes
    NormalVariate
  22. val mu: Double

    the mean

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

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

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

    Definition Classes
    AnyRef
  26. def pf(z: Double): Double

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

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

    z

    the mass point whose probability is sought

    Definition Classes
    NormalVariate
  27. 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
  28. def productArity: Int

    Definition Classes
    Normal → Product
  29. def productElement(arg0: Int): Any

    Definition Classes
    Normal → Product
  30. def productIterator: Iterator[Any]

    Definition Classes
    Product
  31. def productPrefix: String

    Definition Classes
    Normal → Product
  32. val r: Random

    Random number stream selected by the stream number

    Random number stream selected by the stream number

    Attributes
    protected
    Definition Classes
    Variate
  33. val sigma2: Double

    the variance (sigma squared)

  34. val stream: Int

    the random number stream

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

    Definition Classes
    AnyRef
  36. def toString(): String

    Definition Classes
    Normal → AnyRef → Any
  37. final def wait(): Unit

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

    Definition Classes
    AnyRef
    Annotations
    @throws()
  39. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()

Deprecated Value Members

  1. def productElements: Iterator[Any]

    Definition Classes
    Product
    Annotations
    @deprecated
    Deprecated

    (Since version 2.8.0) use productIterator instead

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Variate

Inherited from Error

Inherited from AnyRef

Inherited from Any