# Gaussian

#### case class Gaussian(mu: Double, sigma: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with Product with Serializable

Represents a Gaussian distribution over a single real variable.

Linear Supertypes
Serializable, Serializable, Product, Equals, Moments[Double, Double], ContinuousDistr[Double], Rand[Double], Density[Double], AnyRef, Any
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Inherited
1. Gaussian
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 cdf(x: Double): Double

Computes the cumulative density function of the value x.

9. #### def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
10. #### def condition(p: (Double) ⇒ Boolean): Rand[Double]

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

Gets one sample from the distribution.

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

Definition Classes
GaussianRand
12. #### 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
13. #### def entropy: Double

Definition Classes
GaussianMoments
14. #### final def eq(arg0: AnyRef): Boolean

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

Definition Classes
Rand
16. #### def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
17. #### 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
18. #### 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
19. #### def get(): Double

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

Definition Classes
AnyRef → Any
21. #### def icdf(p: Double): Double

Computes the inverse cdf of the p-value for this gaussian.

Computes the inverse cdf of the p-value for this gaussian.

returns

x s.t. cdf(x) = numYes

22. #### final def isInstanceOf[T0]: Boolean

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

Returns the log unnormalized value of the measure

Returns the log unnormalized value of the measure

Definition Classes
ContinuousDistrDensity
24. #### val logNormalizer: Double

Definition Classes
GaussianContinuousDistr
25. #### def logPdf(x: Double): Double

Definition Classes
ContinuousDistr
26. #### 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
27. #### def mean: Double

Definition Classes
GaussianMoments
28. #### def mode: Double

Definition Classes
GaussianMoments

30. #### final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef

32. #### final def notify(): Unit

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

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

Returns the probability density function at that point.

Returns the probability density function at that point.

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

Gets n samples from the distribution.

Gets n samples from the distribution.

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

Gets one sample from the distribution.

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

Definition Classes
Rand
37. #### 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

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

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

Definition Classes
Gaussian → AnyRef → Any
41. #### def unnormalizedLogPdf(t: Double): Double

Definition Classes
GaussianContinuousDistr
42. #### 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
43. #### def variance: Double

Definition Classes
GaussianMoments
44. #### final def wait(): Unit

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

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

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

Definition Classes
Rand