breeze.stats.distributions

Beta

class Beta extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with HasInverseCdf

The Beta distribution, which is the conjugate prior for the Bernoulli distribution

Linear Supertypes
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Inherited
  1. Beta
  2. HasInverseCdf
  3. HasCdf
  4. Moments
  5. ContinuousDistr
  6. Rand
  7. Serializable
  8. Serializable
  9. Density
  10. AnyRef
  11. Any
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Instance Constructors

  1. new Beta(a: Double, b: Double)(implicit rand: RandBasis = Rand)

    a

    the number of pseudo-observations for true

    b

    the number of pseudo-observations for false

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

    Definition Classes
    BetaHasCdf
  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
    BetaRand
  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
    BetaMoments
  14. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  15. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  16. def filter(p: (Double) ⇒ Boolean): Rand[Double]

    Definition Classes
    Rand
  17. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any
  22. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  23. def inverseCdf(p: Double): Double

    Definition Classes
    BetaHasInverseCdf
  24. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  25. def logApply(x: Double): Double

    Returns the log unnormalized value of the measure

    Returns the log unnormalized value of the measure

    Definition Classes
    ContinuousDistrDensity
  26. lazy val logNormalizer: Double

    Definition Classes
    BetaContinuousDistr
  27. def logPdf(x: Double): Double

    Definition Classes
    ContinuousDistr
  28. 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
  29. def mean: Double

    Definition Classes
    BetaMoments
  30. def mode: Double

    Definition Classes
    BetaMoments
  31. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  32. lazy val normalizer: Double

    Definition Classes
    ContinuousDistr
  33. final def notify(): Unit

    Definition Classes
    AnyRef
  34. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  35. def pdf(x: Double): Double

    Returns the probability density function at that point.

    Returns the probability density function at that point.

    Definition Classes
    BetaContinuousDistr
  36. def probability(x: Double, y: Double): Double

    Definition Classes
    BetaHasCdf
  37. def sample(n: Int): IndexedSeq[Double]

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes
    Rand
  38. def sample(): Double

    Gets one sample from the distribution.

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

    Definition Classes
    Rand
  39. 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
  40. def samplesVector[U >: Double](size: Int)(implicit m: ClassTag[U]): DenseVector[U]

    Return a vector of samples.

    Return a vector of samples.

    Definition Classes
    Rand
  41. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  42. def toString(): String

    Definition Classes
    AnyRef → Any
  43. def unnormalizedLogPdf(x: Double): Double

    Definition Classes
    BetaContinuousDistr
  44. 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
  45. def variance: Double

    Definition Classes
    BetaMoments
  46. final def wait(): Unit

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

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

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

    Definition Classes
    Rand

Inherited from HasInverseCdf

Inherited from HasCdf

Inherited from Moments[Double, Double]

Inherited from ContinuousDistr[Double]

Inherited from Rand[Double]

Inherited from Serializable

Inherited from Serializable

Inherited from Density[Double]

Inherited from AnyRef

Inherited from Any

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