breeze.stats.distributions

Poisson

case class Poisson(mean: Double)(implicit rand: RandBasis = Rand) extends DiscreteDistr[Int] with Moments[Double, Double] with Product with Serializable

Represents a Poisson random variable.

Linear Supertypes
Serializable, Serializable, Product, Equals, Moments[Double, Double], DiscreteDistr[Int], Rand[Int], Density[Int], AnyRef, Any
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Inherited
  1. Poisson
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Moments
  7. DiscreteDistr
  8. Rand
  9. Density
  10. AnyRef
  11. Any
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Instance Constructors

  1. new Poisson(mean: Double)(implicit rand: RandBasis = Rand)

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. def apply(x: Int): Double

    Returns the unnormalized value of the measure

    Returns the unnormalized value of the measure

    Definition Classes
    DiscreteDistrDensity
  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  8. def cdf(k: Int): Double

  9. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. def condition(p: (Int) ⇒ Boolean): Rand[Int]

    Definition Classes
    Rand
  11. def draw(): Int

    Gets one sample from the distribution.

    Gets one sample from the distribution. Equivalent to sample()

    Definition Classes
    PoissonRand
  12. def drawOpt(): Option[Int]

    Overridden by filter/map/flatmap for monadic invocations.

    Overridden by filter/map/flatmap for monadic invocations. Basically, rejeciton samplers will return None here

    Definition Classes
    Rand
  13. def entropy: Double

    Approximate, slow to compute

    Approximate, slow to compute

    Definition Classes
    PoissonMoments
  14. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  15. def filter(p: (Int) ⇒ Boolean): Rand[Int]

    Definition Classes
    Rand
  16. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  17. def flatMap[E](f: (Int) ⇒ Rand[E]): Rand[E]

    Converts a random sampler of one type to a random sampler of another type.

    Converts a random sampler of one type to a random sampler of another type. Examples: randInt(10).flatMap(x => randInt(3 * x.asInstanceOf[Int]) gives a Rand[Int] in the range [0,30] Equivalently, for(x <- randInt(10); y <- randInt(30 *x)) yield y

    f

    the transform to apply to the sampled value.

    Definition Classes
    Rand
  18. def foreach(f: (Int) ⇒ Unit): Unit

    Samples one element and qpplies the provided function to it.

    Samples one element and qpplies the provided function to it. Despite the name, the function is applied once. Sample usage:

     for(x <- Rand.uniform) { println(x) } 
    

    f

    the function to be applied

    Definition Classes
    Rand
  19. def get(): Int

    Definition Classes
    Rand
  20. final def getClass(): Class[_]

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

    Definition Classes
    Any
  22. def logApply(x: Int): Double

    Returns the log unnormalized value of the measure

    Returns the log unnormalized value of the measure

    Definition Classes
    DiscreteDistrDensity
  23. def logProbabilityOf(k: Int): Double

    Definition Classes
    PoissonDiscreteDistr
  24. def map[E](f: (Int) ⇒ E): Rand[E]

    Converts a random sampler of one type to a random sampler of another type.

    Converts a random sampler of one type to a random sampler of another type. Examples: uniform.map(_*2) gives a Rand[Double] in the range [0,2] Equivalently, for(x <- uniform) yield 2*x

    f

    the transform to apply to the sampled value.

    Definition Classes
    Rand
  25. val mean: Double

    Definition Classes
    PoissonMoments
  26. def mode: Double

    Definition Classes
    PoissonMoments
  27. final def ne(arg0: AnyRef): Boolean

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

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

    Definition Classes
    AnyRef
  30. def probabilityOf(k: Int): Double

    Returns the probability of that draw.

    Returns the probability of that draw.

    Definition Classes
    PoissonDiscreteDistr
  31. def sample(n: Int): IndexedSeq[Int]

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes
    Rand
  32. def sample(): Int

    Gets one sample from the distribution.

    Gets one sample from the distribution. Equivalent to get()

    Definition Classes
    Rand
  33. def samples: Iterator[Int]

    An infinitely long iterator that samples repeatedly from the Rand

    An infinitely long iterator that samples repeatedly from the Rand

    returns

    an iterator that repeatedly samples

    Definition Classes
    Rand
  34. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  35. def toString(): String

    Definition Classes
    Poisson → AnyRef → Any
  36. def unnormalizedLogProbabilityOf(x: Int): Double

    Definition Classes
    DiscreteDistr
  37. def unnormalizedProbabilityOf(x: Int): Double

    Returns the probability of that draw up to a constant

    Returns the probability of that draw up to a constant

    Definition Classes
    DiscreteDistr
  38. def variance: Double

    Definition Classes
    PoissonMoments
  39. final def wait(): Unit

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  42. def withFilter(p: (Int) ⇒ Boolean): Rand[Int]

    Definition Classes
    Rand

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Moments[Double, Double]

Inherited from DiscreteDistr[Int]

Inherited from Rand[Int]

Inherited from Density[Int]

Inherited from AnyRef

Inherited from Any

Ungrouped