breeze.stats.distributions

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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Instance Constructors

  1. new Gaussian(mu: Double, sigma: Double)(implicit 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: 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
  29. val mu: Double

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

    Definition Classes
    AnyRef
  31. val normalizer: Double

  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
  38. val sigma: Double

  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

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Moments[Double, Double]

Inherited from ContinuousDistr[Double]

Inherited from Rand[Double]

Inherited from Density[Double]

Inherited from AnyRef

Inherited from Any

Ungrouped