# NegativeBinomial

#### case class NegativeBinomial(r: Double, p: Double) extends DiscreteDistr[Int] with Product with Serializable

Negative Binomial Distribution

r

number of failures until stop

p

prob of success

Linear Supertypes
Serializable, Serializable, Product, Equals, DiscreteDistr[Int], Rand[Int], Density[Int], AnyRef, Any
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Inherited
1. NegativeBinomial
2. Serializable
3. Serializable
4. Product
5. Equals
6. DiscreteDistr
7. Rand
8. Density
9. AnyRef
10. Any
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Visibility
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### Instance Constructors

1. #### new NegativeBinomial(r: Double, p: Double)

r

number of failures until stop

p

prob of success

### 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: Int): 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: (Int) ⇒ Boolean): Rand[Int]

Definition Classes
Rand
10. #### def draw(): Int

Gets one sample from the distribution.

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

Definition Classes
NegativeBinomialRand
11. #### def drawOpt(): Option[Int]

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 filter(p: (Int) ⇒ Boolean): Rand[Int]

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: (Int) ⇒ 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: (Int) ⇒ 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(): Int

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

Definition Classes
AnyRef → Any
19. #### final def isInstanceOf[T0]: Boolean

Definition Classes
Any
20. #### def logApply(x: Int): Double

Returns the log unnormalized value of the measure

Returns the log unnormalized value of the measure

Definition Classes
DiscreteDistrDensity
21. #### def logProbabilityOf(k: Int): Double

Definition Classes
NegativeBinomialDiscreteDistr
22. #### def map[E](f: (Int) ⇒ 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. #### final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
24. #### final def notify(): Unit

Definition Classes
AnyRef
25. #### final def notifyAll(): Unit

Definition Classes
AnyRef
26. #### val p: Double

prob of success

27. #### def probabilityOf(x: Int): Double

Returns the probability of that draw.

Returns the probability of that draw.

Definition Classes
NegativeBinomialDiscreteDistr
28. #### val r: Double

number of failures until stop

29. #### def sample(n: Int): IndexedSeq[Int]

Gets n samples from the distribution.

Gets n samples from the distribution.

Definition Classes
Rand
30. #### def sample(): Int

Gets one sample from the distribution.

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

Definition Classes
Rand
31. #### def samples: Iterator[Int]

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

Definition Classes
AnyRef
33. #### def unnormalizedLogProbabilityOf(x: Int): Double

Definition Classes
DiscreteDistr
34. #### def unnormalizedProbabilityOf(x: Int): Double

Returns the probability of that draw up to a constant

Returns the probability of that draw up to a constant

Definition Classes
DiscreteDistr
35. #### final def wait(): Unit

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

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

Definition Classes
AnyRef
Annotations
@throws( ... )
38. #### def withFilter(p: (Int) ⇒ Boolean): Rand[Int]

Definition Classes
Rand