Trait opensrdk_probability::distribution::Distribution

pub trait Distribution: Clone + Debug + Send + Sync {
    type Value: RandomVariable;
    type Condition: Clone + Debug + Send + Sync;

    // Required method
    fn p_kernel(
        &self,
        x: &Self::Value,
        theta: &Self::Condition
    ) -> Result<f64, DistributionError>;
}

Expand description

The trait which all structs of distribution must implement.

fk: The kernel part of probability density function f. The kernel means that it doesn’t need normalization term of probability density function.

Required Associated Types§

type Value: RandomVariable

type Condition: Clone + Debug + Send + Sync

Required Methods§

fn p_kernel(
&self,
x: &Self::Value,
theta: &Self::Condition
) -> Result<f64, DistributionError>

Implementors§

impl Distribution for Dirichlet

type Value = Vec<f64, Global>

type Condition = DirichletParams

impl Distribution for Beta

type Value = f64

type Condition = BetaParams

impl Distribution for Cauchy

type Value = f64

type Condition = CauchyParams

impl Distribution for Normal

type Value = f64

type Condition = NormalParams

impl Distribution for StudentT

type Value = f64

type Condition = StudentTParams

impl Distribution for Exp

type Value = f64

type Condition = ExpParams

impl Distribution for FisherF

type Value = f64

type Condition = FisherFParams

impl Distribution for InverseWishart

type Value = PPTRF<f64>

type Condition = InverseWishartParams

impl Distribution for NormalInverseWishart

type Value = ExactEllipticalParams

type Condition = NormalInverseWishartParams

impl Distribution for Wishart

type Value = PPTRF<f64>

type Condition = WishartParams

impl Distribution for ChiSquared

type Value = f64

type Condition = ChiSquaredParams

impl Distribution for Gamma

type Value = f64

type Condition = GammaParams

impl Distribution for ContinuousUniform

p returns the constant multiplied value so it can be used only for MCMC.

type Value = f64

type Condition = Range<f64>

impl Distribution for Geometric

type Value = u64

type Condition = GeometricParams

impl Distribution for Bernoulli

type Value = bool

type Condition = BernoulliParams

impl Distribution for Categorical

type Value = usize

type Condition = CategoricalParams

impl Distribution for Binomial

type Value = u64

type Condition = BinomialParams

impl Distribution for Multinominal

type Value = u64

type Condition = MultinomialParams

impl Distribution for Poisson

type Value = u64

type Condition = PoissonParams

impl Distribution for StickBreakingProcess

type Value = Vec<f64, Global>

type Condition = StickBreakingProcessParams

impl<'a, D, T, U> Distribution for SwitchedDistribution<'a, D, T, U>where
D: Distribution<Value = T, Condition = U>,
T: RandomVariable,
U: Event,

type Value = T

type Condition = SwitchedParams<U>

impl<'a, G0, TH> Distribution for PitmanYorGibbs<'a, G0, TH>where
G0: Distribution<Value = TH, Condition = ()>,
TH: RandomVariable,

type Value = PitmanYorGibbsSample

type Condition = PitmanYorGibbsParams<'a, G0, TH>

impl<D, T1, T2, U, F> Distribution for ValuedDistribution<D, T1, T2, U, F>where
D: Distribution<Value = T1, Condition = U>,
T1: RandomVariable,
T2: RandomVariable,
U: Event,
F: Fn(&T2) -> Result<T1, DistributionError> + Clone + Send + Sync,

type Value = T2

type Condition = U

impl<D, T1, T2, U, F, G> Distribution for ValueDifferentiableValuedDistribution<D, T1, T2, U, F, G>where
D: Distribution<Value = T1, Condition = U>,
T1: RandomVariable,
T2: RandomVariable,
U: Event,
F: Fn(&T2) -> Result<T1, DistributionError> + Clone + Send + Sync,
G: Fn(&T2) -> Matrix + Clone + Send + Sync,

type Value = T2

type Condition = U

impl<D, T, U1, U2, F> Distribution for ConditionedDistribution<D, T, U1, U2, F>where
D: Distribution<Value = T, Condition = U1>,
T: RandomVariable,
U1: Event,
U2: Event,
F: Fn(&U2) -> Result<U1, DistributionError> + Clone + Send + Sync,

type Value = T

type Condition = U2

impl<D, T, U1, U2, F, G> Distribution for ConditionDifferentiableConditionedDistribution<D, T, U1, U2, F, G>where
D: Distribution<Value = T, Condition = U1>,
T: RandomVariable,
U1: Event,
U2: Event,
F: Fn(&U2) -> Result<U1, DistributionError> + Clone + Send + Sync,
G: Fn(&U2) -> Matrix + Clone + Send + Sync,

type Value = T

type Condition = U2

impl<D, T, U> Distribution for IndependentArrayJoint<D, T, U>where
D: Distribution<Value = T, Condition = U>,
T: RandomVariable,
U: RandomVariable,

type Value = Vec<T, Global>

type Condition = Vec<U, Global>

impl<D, T, U> Distribution for IndependentValueArrayJoint<D, T, U>where
D: Distribution<Value = T, Condition = U>,
T: RandomVariable,
U: RandomVariable,

type Value = Vec<T, Global>

type Condition = U

impl<D, T, U, V> Distribution for TransformedDistribution<D, T, U, V>where
D: Distribution<Value = T, Condition = U>,
T: RandomVariable,
U: RandomVariable,
V: RandomVariable,

type Value = (T, V)

type Condition = (U, V)

impl<L, P, A, B> Distribution for DiscretePosterior<L, P, A, B>where
L: Distribution<Value = A, Condition = B>,
P: Distribution<Value = B, Condition = ()>,
A: RandomVariable,
B: RandomVariable + Eq + Hash,

type Value = B

type Condition = A

impl<L, R, T, UL, UR> Distribution for DependentJoint<L, R, T, UL, UR>where
L: Distribution<Value = T, Condition = UL>,
R: Distribution<Value = UL, Condition = UR>,
T: RandomVariable,
UL: RandomVariable,
UR: Event,

type Value = (T, UL)

type Condition = UR

impl<L, R, TL, TR, U> Distribution for IndependentJoint<L, R, TL, TR, U>where
L: Distribution<Value = TL, Condition = U>,
R: Distribution<Value = TR, Condition = U>,
TL: RandomVariable,
TR: RandomVariable,
U: Event,

type Value = (TL, TR)

type Condition = U

impl<S, A, K> Distribution for GeneralizedKernelDensityEstimation<S, A, K>where
S: RandomVariable,
A: RandomVariable,
K: PositiveDefiniteKernel<Vec<f64>>,

type Value = A

type Condition = S

impl<T> Distribution for MultivariateCauchy<T>where
T: EllipticalParams,

type Value = Vec<f64, Global>

type Condition = T

impl<T> Distribution for MultivariateNormal<T>where
T: EllipticalParams,

type Value = Vec<f64, Global>

type Condition = T

impl<T> Distribution for DiscreteUniform<T>where
T: RandomVariable + Eq + Hash,

type Value = T

type Condition = HashSet<T, RandomState>

impl<T> Distribution for ContinuousSamplesDistribution<T>where
T: RandomVariable + PartialEq,

type Value = T

type Condition = ()

impl<T> Distribution for Degenerate<T>where
T: RandomVariable + PartialEq,

type Value = T

type Condition = ()

impl<T> Distribution for DiscreteSamplesDistribution<T>where
T: RandomVariable + Eq + Hash,

type Value = T

type Condition = ()

impl<T, U> Distribution for MultivariateStudentT<T, U>where
T: MultivariateStudentTParams<U>,
U: EllipticalParams,

type Value = Vec<f64, Global>

type Condition = T

impl<T, U, FF, FS> Distribution for InstantDistribution<T, U, FF, FS>where
T: RandomVariable,
U: RandomVariable,
FF: Fn(&T, &U) -> Result<f64, DistributionError> + Clone + Send + Sync,
FS: Fn(&U, &mut dyn RngCore) -> Result<T, DistributionError> + Clone + Send + Sync,

type Value = T

type Condition = U

impl<T, U, FF, FS, G> Distribution for ConditionDifferentiableInstantDistribution<T, U, FF, FS, G>where
T: RandomVariable,
U: RandomVariable,
FF: Fn(&T, &U) -> Result<f64, DistributionError> + Clone + Send + Sync,
FS: Fn(&U, &mut dyn RngCore) -> Result<T, DistributionError> + Clone + Send + Sync,
G: Fn(&T, &U) -> Result<Vec<f64>, DistributionError> + Clone + Send + Sync,

type Value = T

type Condition = U

impl<T, U, FF, FS, G> Distribution for ValueDifferentiableInstantDistribution<T, U, FF, FS, G>where
T: RandomVariable,
U: RandomVariable,
FF: Fn(&T, &U) -> Result<f64, DistributionError> + Clone + Send + Sync,
FS: Fn(&U, &mut dyn RngCore) -> Result<T, DistributionError> + Clone + Send + Sync,
G: Fn(&T, &U) -> Result<Vec<f64>, DistributionError> + Clone + Send + Sync,

type Value = T

type Condition = U