distributions

Type Members

1. case class AliasTable[I](probs: DenseVector[Double], aliases: DenseVector[Int], outcomes: IndexedSeq[I], rand: RandBasis) extends Product with Serializable

2. trait ApacheContinuousDistribution extends ContinuousDistr[Double] with HasCdf with HasInverseCdf

3. trait ApacheDiscreteDistribution extends DiscreteDistr[Int]

4. class Bernoulli extends DiscreteDistr[Boolean] with Moments[Double, Double]

5. 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

6. case class Binomial(n: Int, p: Double)(implicit rand: RandBasis = Rand) extends DiscreteDistr[Int] with Moments[Double, Double] with Product with Serializable

   A binomial distribution returns how many coin flips out of n are heads, where numYes is the probability of any one coin being heads.

7. class CauchyDistribution extends ApacheContinuousDistribution

   The Cauchy-distribution

8. case class ChiSquared(k: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with HasInverseCdf with Product with Serializable

   Chi-Squared distribution with k degrees of freedom.

9. trait ContinuousDistr[T] extends Density[T] with Rand[T]

   Represents a continuous Distribution.

10. trait ContinuousDistributionUFuncProvider[T, D <: ContinuousDistr[T]] extends UFunc with MappingUFunc

11. trait Density[T] extends AnyRef

    Represents an unnormalized probability distribution.

12. case class Dirichlet[T, I](params: T)(implicit space: EnumeratedCoordinateField[T, I, Double], rand: RandBasis = Rand) extends ContinuousDistr[T] with Product with Serializable

    Represents a Dirichlet distribution, the conjugate prior to the multinomial.

13. trait DiscreteDistr[T] extends Density[T] with Rand[T]

    Represents a discrete Distribution.

14. case class Exponential(rate: Double)(implicit basis: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with HasInverseCdf with Product with Serializable

15. trait ExponentialFamily[D, T] extends AnyRef

16. class FDistribution extends ApacheContinuousDistribution

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

17. case class Gamma(shape: Double, scale: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with HasInverseCdf with Product with Serializable

    Represents a Gamma distribution.

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

    Represents a Gaussian distribution over a single real variable.

19. case class Geometric(p: Double)(implicit rand: RandBasis = Rand) extends DiscreteDistr[Int] with Moments[Double, Double] with Product with Serializable

    The Geometric distribution calculates the number of trials until the first success, which happens with probability p.

20. case class Gumbel(location: Double, scale: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with Product with Serializable

    TODO

21. trait HasCdf extends AnyRef

22. trait HasConjugatePrior[Likelihood <: Density[T], T] extends ExponentialFamily[Likelihood, T]

    Trait representing conjugate priors.

23. trait HasInverseCdf extends AnyRef

24. class HypergeometricDistribution extends ApacheDiscreteDistribution

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

25. case class Laplace(location: Double, scale: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with Product with Serializable

    http://en.

26. class LevyDistribution extends ApacheContinuousDistribution

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

27. case class LogNormal(mu: Double, sigma: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with HasInverseCdf with Product with Serializable

    A log normal distribution is distributed such that log X ~ Normal(\mu, \sigma)

28. case class Logarthmic(p: Double)(implicit rand: RandBasis = Rand) extends DiscreteDistr[Int] with Moments[Double, Double] with Product with Serializable

    The Logarithmic distribution

29. trait Moments[Mean, Variance] extends AnyRef

    Interface for distributions that can report on some of their moments

30. case class Multinomial[T, I](params: T)(implicit ev: (T) ⇒ QuasiTensor[I, Double], sumImpl: linalg.sum.Impl[T, Double], rand: RandBasis = Rand) extends DiscreteDistr[I] with Product with Serializable

    Represents a Multinomial distribution over elements.

31. case class MultivariateGaussian(mean: DenseVector[Double], covariance: DenseMatrix[Double])(implicit rand: RandBasis = Rand) extends ContinuousDistr[DenseVector[Double]] with Moments[DenseVector[Double], DenseMatrix[Double]] with Product with Serializable

    Represents a Gaussian distribution over a single real variable.

32. case class NegativeBinomial(r: Double, p: Double)(implicit rand: RandBasis = Rand) extends DiscreteDistr[Int] with Product with Serializable

    Negative Binomial Distribution

33. case class Pareto(scale: Double, shape: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with Product with Serializable

    http://en.

34. trait PdfIsUFunc[U <: UFunc, T, P <: PdfIsUFunc[U, T, P]] extends AnyRef

35. case class Poisson(mean: Double)(implicit rand: RandBasis = Rand) extends DiscreteDistr[Int] with Moments[Double, Double] with Product with Serializable

    Represents a Poisson random variable.

36. class Polya[T, I] extends DiscreteDistr[I]

    Represents a Polya distribution, a.

37. trait Process[T] extends Rand[T]

    A Rand that changes based on previous draws.

38. trait Rand[+T] extends Serializable

    A trait for monadic distributions.

39. class RandBasis extends Serializable

    Provides standard combinators and such to use to compose new Rands.

40. case class Rayleigh(scale: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with Product with Serializable

    TODO

41. case class StudentsT(degreesOfFreedom: Double)(implicit randBasis: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with Product with Serializable

    Implements Student's T distribution http://en.wikipedia.org/wiki/Student's_t-distribution

42. trait SufficientStatistic[T <: SufficientStatistic[T]] extends AnyRef

43. class ThreadLocalRandomGenerator extends RandomGenerator

    TODO

44. class TriangularDistribution extends ApacheContinuousDistribution with Moments[Double, Double]

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

45. case class Uniform(low: Double, high: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with HasCdf with HasInverseCdf with Product with Serializable

46. class VariableKernelEmpiricalDistribution extends ApacheContinuousDistribution

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

47. case class VonMises(mu: Double, k: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with Product with Serializable

    Represents a Von Mises distribution, which is a distribution over angles.

48. case class Wald(mean: Double, shape: Double)(implicit rand: RandBasis = Rand) extends ContinuousDistr[Double] with Moments[Double, Double] with Product with Serializable

    Also known as the inverse Gaussian Distribution

49. class WeibullDistribution extends ApacheContinuousDistribution

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

50. class ZipfDistribution extends ApacheDiscreteDistribution