Struct ppca::PosteriorSampler

pub struct PosteriorSampler { /* private fields */ }

Samples from the posterior distribution of an infered sample. The sample is smoothed, that is, it does not include the model isotropic noise.

Trait Implementations

impl Distribution<Matrix<f64, Dynamic, Const<1>, VecStorage<f64, Dynamic, Const<1>>>> for PosteriorSampler

fn sample<R>(&self, rng: &mut R) -> DVector<f64>where
    R: Rng + ?Sized,

Generate a random value of T, using rng as the source of randomness.

fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T>where
    R: Rng,
    Self: Sized,

Create an iterator that generates random values of T, using rng as the source of randomness.

fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S>where
    F: Fn(T) -> S,
    Self: Sized,

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F