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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1. Multinomial
2. Serializable
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4. Product
5. Equals
6. DiscreteDistr
7. Rand
8. Density
9. AnyRef
10. Any
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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

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

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

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