breeze.stats.distributions

Multinomial

case class Multinomial[T, I](params: T)(implicit ev: (T) ⇒ QuasiTensor[I, 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
Serializable, Serializable, Product, Equals, DiscreteDistr[I], Rand[I], Density[I], AnyRef, Any
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Inherited
  1. Multinomial
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. DiscreteDistr
  7. Rand
  8. Density
  9. AnyRef
  10. Any
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  1. Public
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Instance Constructors

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

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: I): Double

    Returns the unnormalized value of the measure

    Returns the unnormalized value of the measure

    Definition Classes
    DiscreteDistrDensity
  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: (I) ⇒ Boolean): Rand[I]

    Definition Classes
    Rand
  10. def draw(): I

    Gets one sample from the distribution.

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

    Definition Classes
    MultinomialRand
  11. def drawOpt(): Option[I]

    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. final def eq(arg0: AnyRef): Boolean

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

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

    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: (I) ⇒ 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: (I) ⇒ 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(): I

    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: I): Double

    Returns the log unnormalized value of the measure

    Returns the log unnormalized value of the measure

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

    Definition Classes
    DiscreteDistr
  23. def map[E](f: (I) ⇒ 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. val params: T

  28. def probabilityOf(e: I): Double

    Returns the probability of that draw.

    Returns the probability of that draw.

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

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes
    Rand
  30. def sample(): I

    Gets one sample from the distribution.

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

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

    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
  32. val sum: Double

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

    Definition Classes
    AnyRef
  34. def toString(): String

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

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

    Returns the probability of that draw up to a constant

    Returns the probability of that draw up to a constant

    Definition Classes
    MultinomialDiscreteDistr
  37. final def wait(): Unit

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

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

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

    Definition Classes
    Rand

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from DiscreteDistr[I]

Inherited from Rand[I]

Inherited from Density[I]

Inherited from AnyRef

Inherited from Any

Ungrouped