Bernoulli

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: Boolean): 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 clone(): AnyRef

   

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

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

   

   Definition Classes

   Rand

8. def draw(): Boolean

   

   Gets one sample from the distribution.

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

   Definition Classes

   Bernoulli → Rand

9. def drawOpt(): Option[Boolean]

   

   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

10. def entropy: Double

    

    Definition Classes

    Bernoulli → Moments

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

    

    Definition Classes

    AnyRef

12. def equals(arg0: Any): Boolean

    

    Definition Classes

    AnyRef → Any

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

    

    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: (Boolean) ⇒ 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: (Boolean) ⇒ 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(): Boolean

    

    Definition Classes

    Rand

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

    

    Definition Classes

    AnyRef → Any

19. def hashCode(): Int

    

    Definition Classes

    AnyRef → Any

20. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

21. def logApply(x: Boolean): Double

    

    Returns the log unnormalized value of the measure

    Returns the log unnormalized value of the measure

    Definition Classes

    DiscreteDistr → Density

22. def logProbabilityOf(x: Boolean): Double

    

    Definition Classes

    DiscreteDistr

23. def map[E](f: (Boolean) ⇒ 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

24. def mean: Double

    

    Definition Classes

    Bernoulli → Moments

25. def mode: Double

    

    Definition Classes

    Bernoulli → Moments

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

    

    Definition Classes

    AnyRef

27. final def notify(): Unit

    

    Definition Classes

    AnyRef

28. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

29. def probabilityOf(b: Boolean): Double

    

    Returns the probability of that draw.

    Returns the probability of that draw.

    Definition Classes

    Bernoulli → DiscreteDistr

30. def sample(n: Int): IndexedSeq[Boolean]

    

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes

    Rand

31. def sample(): Boolean

    

    Gets one sample from the distribution.

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

    Definition Classes

    Rand

32. def samples: Iterator[Boolean]

    

    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

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

    

    Return a vector of samples.

    Return a vector of samples.

    Definition Classes

    Rand

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

    

    Definition Classes

    AnyRef

35. def toString(): String

    

    Definition Classes

    Bernoulli → AnyRef → Any

36. def unnormalizedLogProbabilityOf(x: Boolean): Double

    

    Definition Classes

    DiscreteDistr

37. def unnormalizedProbabilityOf(x: Boolean): 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

    Bernoulli → Moments

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: (Boolean) ⇒ Boolean): Rand[Boolean]

    

    Definition Classes

    Rand