Packages

case class Poisson(mu: Double = 2.0, stream: Int = 0) extends Variate with Product with Serializable

This class generates Poisson random variates (discrete). This discrete RV models the number of events in a time interval of unit length.

mu

the mean

stream

the random number stream

See also

http://www.math.uah.edu/stat/poisson/Poisson.html

Linear Supertypes
Serializable, Product, Equals, Variate, Error, AnyRef, Any
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  1. Poisson
  2. Serializable
  3. Product
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  6. Error
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new Poisson(mu: Double = 2.0, stream: Int = 0)

    mu

    the mean

    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[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
  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. final def flaw(method: String, message: String): Unit
    Definition Classes
    Error
  10. def gen: Double

    Determine the next random number for the particular distribution.

    Determine the next random number for the particular distribution.

    Definition Classes
    PoissonVariate
  11. 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
    PoissonVariate
  12. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  13. 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
  14. 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
  15. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  16. val mean: Double

    Precompute the mean for the particular distribution.

    Precompute the mean for the particular distribution.

    Definition Classes
    PoissonVariate
  17. val mu: Double
  18. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  19. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  20. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  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
    PoissonVariate
  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. def productElementNames: Iterator[String]
    Definition Classes
    Product
  24. val r: Random

    Random number stream selected by the stream number

    Random number stream selected by the stream number

    Attributes
    protected
    Definition Classes
    Variate
  25. 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
  26. 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
  27. val stream: Int
  28. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  29. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  30. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  31. 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 Variate

Inherited from Error

Inherited from AnyRef

Inherited from Any

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