Struct opensrdk_probability::continuous::elliptical::normal::multivariate::MultivariateNormal

pub struct MultivariateNormal<T = ExactEllipticalParams>where
    T: EllipticalParams,{ /* private fields */ }

Multivariate normal distribution

Implementations

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

pub fn new() -> Self

Trait Implementations

impl<T, Rhs, URhs> BitAnd<Rhs> for MultivariateNormal<T>where
T: EllipticalParams,
Rhs: Distribution<Value = T, Condition = URhs>,
URhs: RandomVariable,

type Output = DependentJoint<MultivariateNormal<T>, Rhs, Vec<f64, Global>, T, URhs>

The resulting type after applying the & operator.

fn bitand(self, rhs: Rhs) -> Self::Output

Performs the & operation.

impl<T> Clone for MultivariateNormal<T>where
T: EllipticalParams + Clone,

fn clone(&self) -> MultivariateNormal<T>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl ConditionDifferentiableDistribution for MultivariateNormal

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

impl<T> Debug for MultivariateNormal<T>where
T: EllipticalParams + Debug,

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

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

type Value = Vec<f64, Global>

type Condition = T

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

impl<T, Rhs, TRhs> Mul<Rhs> for MultivariateNormal<T>where
T: EllipticalParams,
Rhs: Distribution<Value = TRhs, Condition = T>,
TRhs: RandomVariable,

type Output = IndependentJoint<MultivariateNormal<T>, Rhs, Vec<f64, Global>, TRhs, T>

The resulting type after applying the * operator.

fn mul(self, rhs: Rhs) -> Self::Output

Performs the * operation.

impl SampleableDistribution for MultivariateNormal

fn sample(
&self,
theta: &Self::Condition,
rng: &mut dyn RngCore
) -> Result<Self::Value, DistributionError>

impl ValueDifferentiableDistribution for MultivariateNormal

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