Class/Object

breeze.stats.distributions

Multinomial

Related Docs: object Multinomial | package distributions

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case class Multinomial[T, I](params: T)(implicit ev: (T) ⇒ QuasiTensor[I, Double], sumImpl: linalg.sum.Impl[T, Double], rand: RandBasis = Rand) extends DiscreteDistr[I] with Product with Serializable

Represents a Multinomial distribution over elements. You can make a distribution over any breeze.linalg.QuasiTensor, which includes DenseVectors and Counters.

TODO: I should probably rename this to Discrete or something, since it only handles one draw.

Linear Supertypes
Product, Equals, DiscreteDistr[I], Rand[I], Serializable, Serializable, Density[I], AnyRef, Any
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Inherited
  1. Multinomial
  2. Product
  3. Equals
  4. DiscreteDistr
  5. Rand
  6. Serializable
  7. Serializable
  8. Density
  9. AnyRef
  10. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new Multinomial(params: T)(implicit ev: (T) ⇒ QuasiTensor[I, Double], sumImpl: linalg.sum.Impl[T, Double], rand: RandBasis = Rand)

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Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  4. def apply(x: I): Double

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    Returns the unnormalized value of the measure

    Returns the unnormalized value of the measure

    Definition Classes
    DiscreteDistrDensity
  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @HotSpotIntrinsicCandidate() @throws( ... )
  7. def condition(p: (I) ⇒ Boolean): Rand[I]

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    Definition Classes
    Rand
  8. def draw(): I

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    Gets one sample from the distribution.

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

    Definition Classes
    MultinomialRand
  9. def drawNaive(): I

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  10. def drawOpt(): Option[I]

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    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. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  12. def expectedValue[U](f: (I) ⇒ U)(implicit vs: VectorSpace[U, Double]): U

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

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    Definition Classes
    Rand
  14. def flatMap[E](f: (I) ⇒ Rand[E]): Rand[E]

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    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: (I) ⇒ Unit): Unit

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    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(): I

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

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    Definition Classes
    AnyRef → Any
    Annotations
    @HotSpotIntrinsicCandidate()
  18. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  19. def logApply(x: I): Double

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    Returns the log unnormalized value of the measure

    Returns the log unnormalized value of the measure

    Definition Classes
    DiscreteDistrDensity
  20. def logProbabilityOf(x: I): Double

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    Definition Classes
    DiscreteDistr
  21. def map[E](f: (I) ⇒ E): Rand[E]

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

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

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    Definition Classes
    AnyRef
    Annotations
    @HotSpotIntrinsicCandidate()
  24. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @HotSpotIntrinsicCandidate()
  25. val params: T

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  26. def probabilityOf(e: I): Double

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    Returns the probability of that draw.

    Returns the probability of that draw.

    Definition Classes
    MultinomialDiscreteDistr
  27. def sample(n: Int): IndexedSeq[I]

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    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes
    Rand
  28. def sample(): I

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    Gets one sample from the distribution.

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

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

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

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    Return a vector of samples.

    Return a vector of samples.

    Definition Classes
    Rand
  31. val sum: Double

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

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    Definition Classes
    AnyRef
  33. def toString(): String

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    Definition Classes
    Multinomial → AnyRef → Any
  34. def unnormalizedLogProbabilityOf(x: I): Double

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    Definition Classes
    DiscreteDistr
  35. def unnormalizedProbabilityOf(e: I): Double

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    Returns the probability of that draw up to a constant

    Returns the probability of that draw up to a constant

    Definition Classes
    MultinomialDiscreteDistr
  36. final def wait(arg0: Long, arg1: Int): Unit

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  38. final def wait(): Unit

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

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    Definition Classes
    Rand

Deprecated Value Members

  1. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @Deprecated @deprecated @throws( classOf[java.lang.Throwable] )
    Deprecated

    (Since version ) see corresponding Javadoc for more information.

Inherited from Product

Inherited from Equals

Inherited from DiscreteDistr[I]

Inherited from Rand[I]

Inherited from Serializable

Inherited from Serializable

Inherited from Density[I]

Inherited from AnyRef

Inherited from Any

Ungrouped