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Module for probability distributions and related functions.
Classes
class AutoCompositeTensorDistribution
: Base for CompositeTensor
bijectors with auto-generated TypeSpec
s.
class Autoregressive
: Autoregressive distributions.
class BatchBroadcast
: A distribution that broadcasts an underlying distribution's batch shape.
class BatchReshape
: The Batch-Reshaping distribution.
class Bates
: Bates distribution.
class Bernoulli
: Bernoulli distribution.
class Beta
: Beta distribution.
class BetaBinomial
: Beta-Binomial compound distribution.
class BetaQuotient
: BetaQuotient distribution.
class Binomial
: Binomial distribution.
class Blockwise
: Blockwise distribution.
class Categorical
: Categorical distribution over integers.
class Cauchy
: The Cauchy distribution with location loc
and scale scale
.
class Chi
: Chi distribution.
class Chi2
: Chi2 distribution.
class CholeskyLKJ
: The CholeskyLKJ distribution on cholesky factors of correlation matrices.
class DeterminantalPointProcess
: Determinantal point process (DPP) distribution.
class Deterministic
: Scalar Deterministic
distribution on the real line.
class Dirichlet
: Dirichlet distribution.
class DirichletMultinomial
: Dirichlet-Multinomial compound distribution.
class Distribution
: A generic probability distribution base class.
class DoublesidedMaxwell
: Double-sided Maxwell distribution.
class Empirical
: Empirical distribution.
class ExpGamma
: ExpGamma distribution.
class ExpInverseGamma
: ExpInverseGamma distribution.
class ExpRelaxedOneHotCategorical
: ExpRelaxedOneHotCategorical distribution with temperature and logits.
class Exponential
: Exponential distribution.
class ExponentiallyModifiedGaussian
: Exponentially modified Gaussian distribution.
class FiniteDiscrete
: The finite discrete distribution.
class FlatDirichlet
: Special case of Dirichlet for concentration = 1.
class Gamma
: Gamma distribution.
class GammaGamma
: Gamma-Gamma distribution.
class GaussianProcess
: Marginal distribution of a Gaussian process at finitely many points.
class GaussianProcessRegressionModel
: Posterior predictive distribution in a conjugate GP regression model.
class GeneralizedExtremeValue
: The scalar GeneralizedExtremeValue distribution.
class GeneralizedNormal
: The Generalized Normal distribution.
class GeneralizedPareto
: The Generalized Pareto distribution.
class Geometric
: Geometric distribution.
class Gumbel
: The scalar Gumbel distribution with location loc
and scale
parameters.
class HalfCauchy
: Half-Cauchy distribution.
class HalfNormal
: The Half Normal distribution with scale scale
.
class HalfStudentT
: Half-Student's t distribution.
class HiddenMarkovModel
: Hidden Markov model distribution.
class Horseshoe
: Horseshoe distribution.
class Independent
: Independent distribution from batch of distributions.
class Inflated
: A mixture of a point-mass and another distribution.
class InverseGamma
: InverseGamma distribution.
class InverseGaussian
: Inverse Gaussian distribution.
class JohnsonSU
: Johnson's SU-distribution.
class JointDistribution
: Joint distribution over one or more component distributions.
class JointDistributionCoroutine
: Joint distribution parameterized by a distribution-making generator.
class JointDistributionCoroutineAutoBatched
: Joint distribution parameterized by a distribution-making generator.
class JointDistributionNamed
: Joint distribution parameterized by named distribution-making functions.
class JointDistributionNamedAutoBatched
: Joint distribution parameterized by named distribution-making functions.
class JointDistributionSequential
: Joint distribution parameterized by distribution-making functions.
class JointDistributionSequentialAutoBatched
: Joint distribution parameterized by distribution-making functions.
class Kumaraswamy
: Kumaraswamy distribution.
class LKJ
: The LKJ distribution on correlation matrices.
class LambertWDistribution
: Implements a general heavy-tail Lambert W x F distribution.
class LambertWNormal
: Implements a location-scale heavy-tail Lambert W x Normal distribution.
class Laplace
: The Laplace distribution with location loc
and scale
parameters.
class LinearGaussianStateSpaceModel
: Observation distribution from a linear Gaussian state space model.
class LogLogistic
: The log-logistic distribution.
class LogNormal
: The log-normal distribution.
class Logistic
: The Logistic distribution with location loc
and scale
parameters.
class LogitNormal
: The logit-normal distribution.
class MarkovChain
: Distribution of a sequence generated by a memoryless process.
class Masked
: A distribution that masks invalid underlying distributions.
class MatrixNormalLinearOperator
: The Matrix Normal distribution on n x p
matrices.
class MatrixTLinearOperator
: The Matrix T distribution on n x p
matrices.
class Mixture
: Mixture distribution.
class MixtureSameFamily
: Mixture (same-family) distribution.
class Moyal
: The Moyal distribution with location loc
and scale
parameters.
class Multinomial
: Multinomial distribution.
class MultivariateNormalDiag
: The multivariate normal distribution on R^k
.
class MultivariateNormalDiagPlusLowRank
: The multivariate normal distribution on R^k
.
class MultivariateNormalDiagPlusLowRankCovariance
: The multivariate normal distribution on R^k
.
class MultivariateNormalFullCovariance
: The multivariate normal distribution on R^k
.
class MultivariateNormalLinearOperator
: The multivariate normal distribution on R^k
.
class MultivariateNormalTriL
: The multivariate normal distribution on R^k
.
class MultivariateStudentTLinearOperator
: The [Multivariate Student's t-distribution](
class NegativeBinomial
: NegativeBinomial distribution.
class NoncentralChi2
: Noncentral Chi2 distribution.
class Normal
: The Normal distribution with location loc
and scale
parameters.
class NormalInverseGaussian
: Normal Inverse Gaussian distribution.
class OneHotCategorical
: OneHotCategorical distribution.
class OrderedLogistic
: Ordered logistic distribution.
class PERT
: Modified PERT distribution for modeling expert predictions.
class Pareto
: Pareto distribution.
class PlackettLuce
: Plackett-Luce distribution over permutations.
class Poisson
: Poisson distribution.
class PoissonLogNormalQuadratureCompound
: PoissonLogNormalQuadratureCompound
distribution.
class PowerSpherical
: The Power Spherical distribution over unit vectors on S^{n-1}
.
class ProbitBernoulli
: ProbitBernoulli distribution.
class QuantizedDistribution
: Distribution representing the quantization Y = ceiling(X)
.
class RegisterKL
: Decorator to register a KL divergence implementation function.
class RelaxedBernoulli
: RelaxedBernoulli distribution with temperature and logits parameters.
class RelaxedOneHotCategorical
: RelaxedOneHotCategorical distribution with temperature and logits.
class ReparameterizationType
: Instances of this class represent how sampling is reparameterized.
class Sample
: Distribution over IID samples of a given shape.
class SigmoidBeta
: SigmoidBeta Distribution.
class SinhArcsinh
: The SinhArcsinh transformation of a distribution on (-inf, inf)
.
class Skellam
: Skellam distribution.
class SphericalUniform
: The uniform distribution over unit vectors on S^{n-1}
.
class StoppingRatioLogistic
: Stopping ratio logistic distribution.
class StudentT
: Student's t-distribution.
class StudentTProcess
: Marginal distribution of a Student's T process at finitely many points.
class StudentTProcessRegressionModel
: StudentTProcessRegressionModel.
class TransformedDistribution
: A Transformed Distribution.
class Triangular
: Triangular distribution with low
, high
and peak
parameters.
class TruncatedCauchy
: The Truncated Cauchy distribution.
class TruncatedNormal
: The Truncated Normal distribution.
class TwoPieceNormal
: The Two-Piece Normal distribution.
class TwoPieceStudentT
: The Two-Piece Student's t-distribution.
class Uniform
: Uniform distribution with low
and high
parameters.
class VariationalGaussianProcess
: Posterior predictive of a variational Gaussian process.
class VectorDeterministic
: Vector Deterministic
distribution on R^k
.
class VonMises
: The von Mises distribution over angles.
class VonMisesFisher
: The von Mises-Fisher distribution over unit vectors on S^{n-1}
.
class Weibull
: The Weibull distribution with 'concentration' and scale
parameters.
class WishartLinearOperator
: The matrix Wishart distribution on positive definite matrices.
class WishartTriL
: The matrix Wishart distribution parameterized with Cholesky factors.
class ZeroInflatedNegativeBinomial
: A mixture of a point-mass and another distribution.
class Zipf
: Zipf distribution.
Functions
independent_joint_distribution_from_structure(...)
: Turns a (potentially nested) structure of dists into a single dist.
kl_divergence(...)
: Get the KL-divergence KL(distribution_a || distribution_b).
mvn_conjugate_linear_update(...)
: Computes a conjugate normal posterior for a Bayesian linear regression.
normal_conjugates_known_scale_posterior(...)
: Posterior Normal distribution with conjugate prior on the mean.
normal_conjugates_known_scale_predictive(...)
: Posterior predictive Normal distribution w. conjugate prior on the mean.
quadrature_scheme_lognormal_gauss_hermite(...)
: Use Gauss-Hermite quadrature to form quadrature on positive-reals.
quadrature_scheme_lognormal_quantiles(...)
: Use LogNormal quantiles to form quadrature on positive-reals.
Other Members | |
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FULLY_REPARAMETERIZED |
Instance of oryx.distributions.ReparameterizationType
|
NOT_REPARAMETERIZED |
Instance of oryx.distributions.ReparameterizationType
|