Wald

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: Double): Double

   Returns the unnormalized value of the measure

   Returns the unnormalized value of the measure

   Definition Classes

   ContinuousDistr → Density

7. final def asInstanceOf[T0]: T0

   Definition Classes

   Any

8. def clone(): AnyRef

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

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

   Definition Classes

   Rand

10. def draw(): Double

    Gets one sample from the distribution.

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

    Definition Classes

    Wald → Rand

11. def drawOpt(): Option[Double]

    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

12. def entropy: Double

    Definition Classes

    Wald → Moments

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

    Definition Classes

    AnyRef

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

    Definition Classes

    Rand

15. def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

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

16. def flatMap[E](f: (Double) ⇒ 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

17. def foreach(f: (Double) ⇒ 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

18. def get(): Double

    Definition Classes

    Rand

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

    Definition Classes

    AnyRef → Any

20. final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

21. def logApply(x: Double): Double

    Returns the log unnormalized value of the measure

    Returns the log unnormalized value of the measure

    Definition Classes

    ContinuousDistr → Density

22. def logNormalizer: Double

    Definition Classes

    Wald → ContinuousDistr

23. def logPdf(x: Double): Double

    Definition Classes

    ContinuousDistr

24. def map[E](f: (Double) ⇒ 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

    Wald → Moments

26. lazy val mode: Double

    Definition Classes

    Wald → Moments

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

    Definition Classes

    AnyRef

28. lazy val normalizer: Double

    Definition Classes

    ContinuousDistr

29. final def notify(): Unit

    Definition Classes

    AnyRef

30. final def notifyAll(): Unit

    Definition Classes

    AnyRef

31. def pdf(x: Double): Double

    Returns the probability density function at that point.

    Returns the probability density function at that point.

    Definition Classes

    ContinuousDistr

32. def sample(n: Int): IndexedSeq[Double]

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes

    Rand

33. def sample(): Double

    Gets one sample from the distribution.

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

    Definition Classes

    Rand

34. def samples: Iterator[Double]

    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

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

    Return a vector of samples.

    Return a vector of samples.

    Definition Classes

    Rand

36. val shape: Double

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

    Definition Classes

    AnyRef

38. def unnormalizedLogPdf(x: Double): Double

    Definition Classes

    Wald → ContinuousDistr

39. def unnormalizedPdf(x: Double): Double

    Returns the probability density function up to a constant at that point.

    Returns the probability density function up to a constant at that point.

    Definition Classes

    ContinuousDistr

40. def variance: Double

    Definition Classes

    Wald → Moments

41. final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

44. def withFilter(p: (Double) ⇒ Boolean): Rand[Double]

    Definition Classes

    Rand