Wald

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: Double): Double

   

   Returns the unnormalized value of the measure

   Returns the unnormalized value of the measure

   Definition Classes

   ContinuousDistr → 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: (Double) ⇒ Boolean): Rand[Double]

   

   Definition Classes

   Rand

8. def draw(): Double

   

   Gets one sample from the distribution.

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

   Definition Classes

   Wald → Rand

9. 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

10. def entropy: Double

    

    Definition Classes

    Wald → Moments

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

    

    Definition Classes

    AnyRef

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

    

    Definition Classes

    Rand

13. def finalize(): Unit

    

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

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

14. 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

15. 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

16. def get(): Double

    

    Definition Classes

    Rand

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

    

    Definition Classes

    AnyRef → Any

18. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

19. 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

20. def logNormalizer: Double

    

    Definition Classes

    Wald → ContinuousDistr

21. def logPdf(x: Double): Double

    

    Definition Classes

    ContinuousDistr

22. 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

23. val mean: Double

    

    Definition Classes

    Wald → Moments

24. lazy val mode: Double

    

    Definition Classes

    Wald → Moments

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

    

    Definition Classes

    AnyRef

26. lazy val normalizer: Double

    

    Definition Classes

    ContinuousDistr

27. final def notify(): Unit

    

    Definition Classes

    AnyRef

28. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

29. def pdf(x: Double): Double

    

    Returns the probability density function at that point.

    Returns the probability density function at that point.

    Definition Classes

    ContinuousDistr

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

    

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes

    Rand

31. def sample(): Double

    

    Gets one sample from the distribution.

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

    Definition Classes

    Rand

32. 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

33. 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

34. val shape: Double

    

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

    

    Definition Classes

    AnyRef

36. def unnormalizedLogPdf(x: Double): Double

    

    Definition Classes

    Wald → ContinuousDistr

37. 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

38. def variance: Double

    

    Definition Classes

    Wald → 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: (Double) ⇒ Boolean): Rand[Double]

    

    Definition Classes

    Rand