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cardano

AllDistributions

class AllDistributions extends DiscreteDistributions with ContinuousDistributions with MetropolisDistributions with PosteriorDistributions

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Inherited
  1. AllDistributions
  2. PosteriorDistributions
  3. MetropolisDistributions
  4. ContinuousDistributions
  5. DiscreteDistributions
  6. Distributions
  7. AnyRef
  8. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new AllDistributions(randomGenerator: RandomGenerator)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def beta(a: Double, b: Double): Stochastic[Double]
    Definition Classes
    ContinuousDistributions
  6. def choose[A](distribution: Dist[A])(implicit ev: (DenseVector[Double]) ⇒ QuasiTensor[Int, Double], sumImpl: breeze.linalg.sum.Impl[DenseVector[Double], Double]): Stochastic[A]
    Definition Classes
    DiscreteDistributions
  7. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. def coin: Stochastic[Boolean]
    Definition Classes
    DiscreteDistributions
  9. def coin(p: Prob = 0.5): Stochastic[Boolean]
    Definition Classes
    DiscreteDistributions
  10. def continuousUniform(a: Double, b: Double): Stochastic[Double]
    Definition Classes
    ContinuousDistributions
  11. def continuousUniform: Stochastic[Double]
    Definition Classes
    ContinuousDistributions
  12. def discreteUniform(n: Int): Stochastic[Int]
    Definition Classes
    DiscreteDistributions
  13. def discreteUniform[A](values: Seq[A]): Stochastic[A]
    Definition Classes
    DiscreteDistributions
  14. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  15. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  16. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  17. def fromMass(mass: Iterable[Prob]): Stochastic[Int]
    Definition Classes
    DiscreteDistributions
  18. def gaussian(mean: Double, std: Double): Stochastic[Double]
    Definition Classes
    ContinuousDistributions
  19. def gaussian: Stochastic[Double]
    Definition Classes
    ContinuousDistributions
  20. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  21. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  22. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  23. def maxEntropy[A](init: Stochastic[A], inverseTemp: Double, burnIn: Int = defaultSampleBurnIn, interval: Int = defaultSampleInterval)(costFunc: (A) ⇒ Double)(symmetricTransitionFunction: (A) ⇒ Stochastic[A]): Stochastic[A]
    Definition Classes
    MetropolisDistributions
  24. def metropolis[A](init: Stochastic[A], burnIn: Int = defaultSampleBurnIn, interval: Int = defaultSampleInterval)(logUnnormalizedProbabilityOf: (A) ⇒ Double)(symmetricTransitionFunction: (A) ⇒ Stochastic[A]): Stochastic[A]
    Definition Classes
    MetropolisDistributions
  25. def metropolisHastings[A](init: Stochastic[A], burnIn: Int = defaultSampleBurnIn, interval: Int = defaultSampleInterval)(logUnnormalizedProbabilityOf: (A) ⇒ Double)(logTransitionFunction: (A) ⇒ Stochastic[(A, Double, Double)]): Stochastic[A]
    Definition Classes
    MetropolisDistributions
  26. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  27. final def notify(): Unit
    Definition Classes
    AnyRef
  28. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  29. def posterior[A, O](prior: Stochastic[A], observations: Seq[O], burnIn: Int = defaultSampleBurnIn, interval: Int = defaultSampleInterval)(likelihood: (A, O) ⇒ Prob): Stochastic[A]
    Definition Classes
    PosteriorDistributions
  30. def posteriorByLog[A, O](prior: Stochastic[A], observations: Seq[O], burnIn: Int = defaultSampleBurnIn, interval: Int = defaultSampleInterval)(logLikelihood: (A, O) ⇒ Double): Stochastic[A]
    Definition Classes
    PosteriorDistributions
  31. val randomGenerator: RandomGenerator
    Definition Classes
    AllDistributionsDistributions
  32. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  33. def toString(): String
    Definition Classes
    AnyRef → Any
  34. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  35. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  36. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from PosteriorDistributions

Inherited from MetropolisDistributions

Inherited from ContinuousDistributions

Inherited from DiscreteDistributions

Inherited from Distributions

Inherited from AnyRef

Inherited from Any

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