Trait rv::traits::Mean

pub trait Mean<X> {
    fn mean(&self) -> Option<X>;
}

Defines the distribution mean

Required methods

fn mean(&self) -> Option<X>

Returns None if the mean is undefined

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Implementors

impl Mean<f32> for Beta

fn mean(&self) -> Option<f32>

impl Mean<f32> for ChiSquared

fn mean(&self) -> Option<f32>

impl Mean<f32> for Exponential

fn mean(&self) -> Option<f32>

impl Mean<f32> for Gamma

fn mean(&self) -> Option<f32>

impl Mean<f32> for Gaussian

fn mean(&self) -> Option<f32>

impl Mean<f32> for Gev

fn mean(&self) -> Option<f32>

impl Mean<f32> for InvChiSquared

fn mean(&self) -> Option<f32>

impl Mean<f32> for InvGamma

fn mean(&self) -> Option<f32>

impl Mean<f32> for InvGaussian

fn mean(&self) -> Option<f32>

impl Mean<f32> for Kumaraswamy

fn mean(&self) -> Option<f32>

impl Mean<f32> for Laplace

fn mean(&self) -> Option<f32>

impl Mean<f32> for LogNormal

fn mean(&self) -> Option<f32>

impl Mean<f32> for Pareto

fn mean(&self) -> Option<f32>

impl Mean<f32> for ScaledInvChiSquared

fn mean(&self) -> Option<f32>

impl Mean<f32> for StudentsT

fn mean(&self) -> Option<f32>

impl Mean<f32> for Uniform

fn mean(&self) -> Option<f32>

impl Mean<f32> for VonMises

fn mean(&self) -> Option<f32>

impl Mean<f64> for Bernoulli

fn mean(&self) -> Option<f64>

impl Mean<f64> for Beta

fn mean(&self) -> Option<f64>

impl Mean<f64> for BetaBinomial

fn mean(&self) -> Option<f64>

impl Mean<f64> for Binomial

fn mean(&self) -> Option<f64>

impl Mean<f64> for ChiSquared

fn mean(&self) -> Option<f64>

impl Mean<f64> for Empirical

fn mean(&self) -> Option<f64>

impl Mean<f64> for Exponential

fn mean(&self) -> Option<f64>

impl Mean<f64> for Gamma

fn mean(&self) -> Option<f64>

impl Mean<f64> for Gaussian

fn mean(&self) -> Option<f64>

impl Mean<f64> for Geometric

fn mean(&self) -> Option<f64>

impl Mean<f64> for Gev

fn mean(&self) -> Option<f64>

impl Mean<f64> for InvChiSquared

fn mean(&self) -> Option<f64>

impl Mean<f64> for InvGamma

fn mean(&self) -> Option<f64>

impl Mean<f64> for InvGaussian

fn mean(&self) -> Option<f64>

impl Mean<f64> for Kumaraswamy

fn mean(&self) -> Option<f64>

impl Mean<f64> for Laplace

fn mean(&self) -> Option<f64>

impl Mean<f64> for LogNormal

fn mean(&self) -> Option<f64>

impl Mean<f64> for NegBinomial

fn mean(&self) -> Option<f64>

impl Mean<f64> for Pareto

fn mean(&self) -> Option<f64>

impl Mean<f64> for Poisson

fn mean(&self) -> Option<f64>

impl Mean<f64> for ScaledInvChiSquared

fn mean(&self) -> Option<f64>

impl Mean<f64> for Skellam

fn mean(&self) -> Option<f64>

impl Mean<f64> for StudentsT

fn mean(&self) -> Option<f64>

impl Mean<f64> for Uniform

fn mean(&self) -> Option<f64>

impl Mean<f64> for VonMises

fn mean(&self) -> Option<f64>

impl Mean<Matrix<f64, Dynamic, Dynamic, <DefaultAllocator as Allocator<f64, Dynamic, Dynamic>>::Buffer>> for InvWishart

fn mean(&self) -> Option<DMatrix<f64>>

impl Mean<Matrix<f64, Dynamic, U1, VecStorage<f64, Dynamic, U1>>> for MvGaussian

fn mean(&self) -> Option<DVector<f64>>

impl<Fx> Mean<f32> for Mixture<Fx> where
    Fx: Mean<f32>, 

fn mean(&self) -> Option<f32>

impl<Fx> Mean<f64> for Mixture<Fx> where
    Fx: Mean<f64>, 

fn mean(&self) -> Option<f64>

impl<Fx, X> Mean<X> for Fx where
    Fx: Deref,
    Fx::Target: Mean<X>, 

fn mean(&self) -> Option<X>

impl<T> Mean<f64> for DiscreteUniform<T> where
    T: DuParam + SampleUniform + Into<f64>, 

fn mean(&self) -> Option<f64>

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