# Gamma

#### case class Gamma(shape: Double, scale: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with Product with Serializable

Represents a Gamma distribution. E[X] = shape * scale

Linear Supertypes
Serializable, Serializable, Product, Equals, Moments[Double, Double], ContinuousDistr[Double], Rand[Double], Density[Double], AnyRef, Any
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Inherited
1. Gamma
2. Serializable
3. Serializable
4. Product
5. Equals
6. Moments
7. ContinuousDistr
8. Rand
9. Density
10. AnyRef
11. 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: Double): Double

Returns the unnormalized value of the measure

Returns the unnormalized value of the measure

Definition Classes
ContinuousDistrDensity
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: (Double) ⇒ Boolean): Rand[Double]

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

Gets one sample from the distribution.

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

Definition Classes
GammaRand
11. #### def drawOpt(): Option[Double]

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. #### def entropy: Double

Definition Classes
GammaMoments
13. #### final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
14. #### def filter(p: (Double) ⇒ Boolean): Rand[Double]

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: (Double) ⇒ 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: (Double) ⇒ 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(): Double

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: Double): Double

Returns the log unnormalized value of the measure

Returns the log unnormalized value of the measure

Definition Classes
ContinuousDistrDensity

23. #### lazy val logNormalizer: Double

Definition Classes
GammaContinuousDistr
24. #### def logPdf(x: Double): Double

Definition Classes
ContinuousDistr
25. #### def map[E](f: (Double) ⇒ 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
26. #### def mean: Double

Definition Classes
GammaMoments
27. #### def mode: Double

Definition Classes
GammaMoments
28. #### final def ne(arg0: AnyRef): Boolean

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

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

Definition Classes
AnyRef
31. #### def pdf(x: Double): Double

Returns the probability density function at that point.

Returns the probability density function at that point.

Definition Classes
ContinuousDistr
32. #### def sample(n: Int): IndexedSeq[Double]

Gets n samples from the distribution.

Gets n samples from the distribution.

Definition Classes
Rand
33. #### def sample(): Double

Gets one sample from the distribution.

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

Definition Classes
Rand
34. #### def samples: Iterator[Double]

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

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

Definition Classes
AnyRef
38. #### def toString(): String

Definition Classes
Gamma → AnyRef → Any
39. #### def unnormalizedLogPdf(x: Double): Double

Definition Classes
GammaContinuousDistr
40. #### def unnormalizedPdf(x: Double): Double

Returns the probability density function up to a constant at that point.

Returns the probability density function up to a constant at that point.

Definition Classes
ContinuousDistr
41. #### def variance: Double

Definition Classes
GammaMoments
42. #### final def wait(): Unit

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

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

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

Definition Classes
Rand