breeze.stats.distributions

FDistribution

class FDistribution extends ApacheContinuousDistribution

The F-distribution - ratio of two scaled chi^2 variables

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  1. FDistribution
  2. ApacheContinuousDistribution
  3. HasInverseCdf
  4. HasCdf
  5. ContinuousDistr
  6. Rand
  7. Serializable
  8. Serializable
  9. Density
  10. AnyRef
  11. Any
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  1. Public
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Instance Constructors

  1. new FDistribution(numeratorDegreesOfFreedom: Double, denominatorDegreesOfFreedom: Double)

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
    ApacheContinuousDistributionHasCdf
  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
    ApacheContinuousDistributionRand
  12. def drawMany(n: Int): Array[Double]

    Definition Classes
    ApacheContinuousDistribution
  13. 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
  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. final val inner: org.apache.commons.math3.distribution.FDistribution

    Attributes
    protected
    Definition Classes
    FDistributionApacheContinuousDistribution
  24. def inverseCdf(p: Double): Double

  25. final def isInstanceOf[T0]: Boolean

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

    Returns the log unnormalized value of the measure

    Returns the log unnormalized value of the measure

    Definition Classes
    ContinuousDistrDensity
  27. lazy val logNormalizer: Double

  28. def logPdf(x: Double): Double

    Definition Classes
    ContinuousDistr
  29. 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
  30. def mean: Double

    Definition Classes
    ApacheContinuousDistribution
  31. def mode: Double

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

    Definition Classes
    AnyRef
  33. lazy val normalizer: Double

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

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

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

    Returns the probability density function at that point.

    Returns the probability density function at that point.

    Definition Classes
    ApacheContinuousDistributionContinuousDistr
  37. def probability(x: Double, y: Double): Double

    Definition Classes
    ApacheContinuousDistributionHasCdf
  38. def sample(n: Int): IndexedSeq[Double]

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes
    Rand
  39. def sample(): Double

    Gets one sample from the distribution.

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

    Definition Classes
    Rand
  40. 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
  41. 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
  42. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  43. def toString(): String

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

  45. 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
  46. def variance: Double

    Definition Classes
    ApacheContinuousDistribution
  47. final def wait(): Unit

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

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

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

    Definition Classes
    Rand

Inherited from HasInverseCdf

Inherited from HasCdf

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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