Poisson

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. def apply(x: Int): Double

   

   Returns the unnormalized value of the measure

   Returns the unnormalized value of the measure

   Definition Classes

   DiscreteDistr → Density

5. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

6. def cdf(k: Int): Double

   

7. def clone(): AnyRef

   

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

8. def condition(p: (Int) ⇒ Boolean): Rand[Int]

   

   Definition Classes

   Rand

9. def draw(): Int

   

   Gets one sample from the distribution.

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

   Definition Classes

   Poisson → Rand

10. 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

11. def entropy: Double

    

    Approximate, slow to compute

    Approximate, slow to compute

    Definition Classes

    Poisson → Moments

12. final def eq(arg0: AnyRef): Boolean

    

    Definition Classes

    AnyRef

13. def filter(p: (Int) ⇒ Boolean): Rand[Int]

    

    Definition Classes

    Rand

14. def finalize(): Unit

    

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

15. 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

16. 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

17. def get(): Int

    

    Definition Classes

    Rand

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

    

    Definition Classes

    AnyRef → Any

19. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

20. def logApply(x: Int): Double

    

    Returns the log unnormalized value of the measure

    Returns the log unnormalized value of the measure

    Definition Classes

    DiscreteDistr → Density

21. def logProbabilityOf(k: Int): Double

    

    Definition Classes

    Poisson → DiscreteDistr

22. 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

23. val mean: Double

    

    Definition Classes

    Poisson → Moments

24. def mode: Double

    

    Definition Classes

    Poisson → Moments

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

    

    Definition Classes

    AnyRef

26. final def notify(): Unit

    

    Definition Classes

    AnyRef

27. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

28. def probabilityOf(k: Int): Double

    

    Returns the probability of that draw.

    Returns the probability of that draw.

    Definition Classes

    Poisson → DiscreteDistr

29. def sample(n: Int): IndexedSeq[Int]

    

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes

    Rand

30. def sample(): Int

    

    Gets one sample from the distribution.

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

    Definition Classes

    Rand

31. 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

32. def samplesVector[U >: Int](size: Int)(implicit m: ClassTag[U]): DenseVector[U]

    

    Return a vector of samples.

    Return a vector of samples.

    Definition Classes

    Rand

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

    

    Definition Classes

    AnyRef

34. def toString(): String

    

    Definition Classes

    Poisson → AnyRef → Any

35. def unnormalizedLogProbabilityOf(x: Int): Double

    

    Definition Classes

    DiscreteDistr

36. 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

37. def variance: Double

    

    Definition Classes

    Poisson → Moments

38. final def wait(): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

39. final def wait(arg0: Long, arg1: Int): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

40. final def wait(arg0: Long): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

41. def withFilter(p: (Int) ⇒ Boolean): Rand[Int]

    

    Definition Classes

    Rand