breeze.stats.distributions

DiscreteDistr

trait DiscreteDistr[T] extends Measure[T] with Rand[T]

Represents a discrete Distribution.

Linear Supertypes
Rand[T], Measure[T], AnyRef, Any
Known Subclasses
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  1. DiscreteDistr
  2. Rand
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Abstract Value Members

  1. abstract def draw(): T

    Gets one sample from the distribution.

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

    Definition Classes
    Rand
  2. abstract def probabilityOf(x: T): Double

    Returns the probability of that draw.

Concrete 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: T): Double

    Returns the unnormalized value of the measure

    Returns the unnormalized value of the measure

    Definition Classes
    DiscreteDistrMeasure
  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: (T) ⇒ Boolean): Rand[T]

    Definition Classes
    Rand
  10. def drawOpt(): Option[T]

    Overridden by filter/map/flatmap for monadic invocations

    Overridden by filter/map/flatmap for monadic invocations

    Attributes
    protected
    Definition Classes
    Rand
  11. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  12. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  13. def filter(p: (T) ⇒ Boolean): Rand[T]

    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: (T) ⇒ 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: (T) ⇒ 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(): T

    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: T): Double

    Returns the log unnormalized value of the measure

    Returns the log unnormalized value of the measure

    Definition Classes
    DiscreteDistrMeasure
  22. def logProbabilityOf(x: T): Double

  23. def map[E](f: (T) ⇒ 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. final def ne(arg0: AnyRef): Boolean

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

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

    Definition Classes
    AnyRef
  27. def sample(n: Int): IndexedSeq[T]

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes
    Rand
  28. def sample(): T

    Gets one sample from the distribution.

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

    Definition Classes
    Rand
  29. def samples: Iterator[T]

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

    Definition Classes
    AnyRef
  31. def toString(): String

    Definition Classes
    AnyRef → Any
  32. def unnormalizedLogProbabilityOf(x: T): Double

  33. def unnormalizedProbabilityOf(x: T): Double

    Returns the probability of that draw up to a constant

  34. final def wait(): Unit

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

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

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

    Definition Classes
    Rand

Inherited from Rand[T]

Inherited from Measure[T]

Inherited from AnyRef

Inherited from Any

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