Package

com.stripe.rainier

core

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package core

Visibility
  1. Public
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Type Members

  1. final case class Bernoulli(p: Real) extends Discrete with Product with Serializable

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    Bernoulli distribution with expectation p

    Bernoulli distribution with expectation p

    p

    The probability of success

  2. final case class Beta(a: Real, b: Real) extends StandardContinuous with Product with Serializable

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    A Beta distribution with expectation a/(a + b) and variance ab/((a + b)^2 (1 + a + b)).

  3. final case class BetaBinomial(a: Real, b: Real, k: Real) extends Discrete with Product with Serializable

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    A Beta-binomial distribution with expectation a/(a + b) * k

  4. final case class Binomial(p: Real, k: Real) extends Discrete with Product with Serializable

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    A Binomial distribution with expectation k*p

    A Binomial distribution with expectation k*p

    p

    The probability of success

    k

    The number of trials

  5. trait Continuous extends Distribution[Double]

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    A Continuous Distribution, with method real allowing conversion to a random variable.

  6. trait Discrete extends Distribution[Long]

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  7. final case class DiscreteConstant(constant: Real) extends Discrete with Product with Serializable

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    Discrete Constant (point mass) with expecation constant

    Discrete Constant (point mass) with expecation constant

    constant

    The integer value of the point mass

  8. final case class DiscreteMixture(components: Map[Discrete, Real]) extends Discrete with Product with Serializable

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    Discrete Mixture Distribution

    Discrete Mixture Distribution

    components

    Map of Discrete distribution and probabilities

  9. trait Distribution[T] extends AnyRef

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  10. sealed trait Generator[+T] extends AnyRef

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    Generator trait, for posterior predictive distributions to be forwards sampled during sampling

  11. final case class Geometric(p: Real) extends Discrete with Product with Serializable

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    Geometric distribution with expectation 1/p

    Geometric distribution with expectation 1/p

    p

    The probability of success

  12. trait LocationScaleFamily extends AnyRef

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    Location-scale family distribution

  13. case class Mixture(components: Map[Continuous, Real]) extends Continuous with Product with Serializable

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  14. class Model extends AnyRef

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  15. final case class Multinomial[T](pmf: Map[T, Real], k: Real) extends Distribution[Map[T, Long]] with Product with Serializable

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    A Multinomial distribution

    A Multinomial distribution

    pmf

    A map with keys corresponding to the possible outcomes of a single multinomial trial and values corresponding to the probabilities of those outcomes

    k

    The number of multinomial trials

  16. final case class NegativeBinomial(p: Real, n: Real) extends Discrete with Product with Serializable

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    Negative Binomial distribution with expectation n*p/(1-p)

    Negative Binomial distribution with expectation n*p/(1-p)

    p

    Probability of success

    n

    Total number of failures

  17. final case class Poisson(lambda: Real) extends Discrete with Product with Serializable

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    Poisson distribution with expectation lambda

    Poisson distribution with expectation lambda

    lambda

    The mean of the Poisson distribution

  18. final case class SBC[T](priors: Seq[Continuous], fn: (Seq[Real]) ⇒ (Distribution[T], Real)) extends Product with Serializable

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  19. final case class Scale(a: Real) extends Injection with Product with Serializable

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    Class to scale a distribution under multiplication by a positive scale factor.

    Class to scale a distribution under multiplication by a positive scale factor. We assume that (a > 0).

  20. trait ToGenerator[-T, U] extends AnyRef

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  21. case class Trace(chains: List[List[Array[Double]]], mass: List[MassMatrix], stats: List[Stats], model: Model)(implicit rng: RNG) extends Product with Serializable

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  22. final case class Translate(b: Real) extends Injection with Product with Serializable

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    Class to translate a distribution by adding a constant.

Value Members

  1. object Beta extends Serializable

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  2. object BetaBinomial extends Serializable

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  3. object Cauchy extends LocationScaleFamily

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    A Cauchy distribution with mode location and scaling relative to standard Cauchy of scale

  4. object Combinatorics

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    Combinatoric functions useful in log density calculations.

    Combinatoric functions useful in log density calculations. Note that they all return the log of the function described.

  5. object Exp extends Injection

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    Object to exponentiate a distribution.

  6. object Exponential

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    An Exponential distribution with expectation 1/rate

  7. object Gamma

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    A Gamma distribution with expectation shape*scale and variance shape*scale*scale.

    A Gamma distribution with expectation shape*scale and variance shape*scale*scale. N.B. It is parameterised with *scale* rather than *rate*, as is more typical in statistics texts.

  8. object Generator

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    Generator object, for posterior predictive distributions to be forwards sampled during sampling

  9. object Laplace extends LocationScaleFamily

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    A Laplace distribution with expectation location and variance 2*scale*scale

  10. object Log extends Logger

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  11. object LogNormal

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    A LogNormal distribution representing the exponential of a Gaussian random variable with expectation location and standard deviation scale.

    A LogNormal distribution representing the exponential of a Gaussian random variable with expectation location and standard deviation scale. It therefore has expectation exp(location + scale*scale/2).

  12. object Model

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  13. object Multinomial extends Serializable

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  14. object Normal extends LocationScaleFamily

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    A Gaussian distribution with expectation location and standard deviation scale

  15. object Poisson extends Serializable

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  16. object SBC extends Serializable

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  17. object ToGenerator

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  18. object Trace extends Serializable

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    This is a direct implementation of the equations described in sections 30.3 (for rHat and v) and 30.4 (for autocorrelation and ess) of the Stan manual.

  19. object Uniform

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    A Uniform distribution over [from,to] with expectation (to-from)/2.

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