Struct MclmcChain 

pub struct MclmcChain<M, R, A, T>
where
    M: Math,
    R: Rng,
    T: Transformation<M>,
    A: AdaptStrategy<M, Hamiltonian = TransformedHamiltonian<M, T>>,
{ /* private fields */ }

Single-chain MCLMC sampler.

Implementations

impl<M, R, A, T> MclmcChain<M, R, A, T>

where M: Math, R: Rng, T: Transformation<M>, A: AdaptStrategy<M, Hamiltonian = TransformedHamiltonian<M, T>>,

pub fn new( math: M, hamiltonian: TransformedHamiltonian<M, T>, adapt: A, rng: R, chain: u64, subsample_frequency: f64, dynamic_step_size: bool, trajectory_kind: MclmcTrajectoryKind, switch_draw: u64, max_energy_error: f64, stats_options: StatOptions<M, A>, ) -> Self

Trait Implementations

impl<M, R, A, T> Chain<M> for MclmcChain<M, R, A, T>

where M: Math, R: Rng, T: Transformation<M>, A: AdaptStrategy<M, Hamiltonian = TransformedHamiltonian<M, T>>,

type AdaptStrategy = A

fn set_position(&mut self, position: &[f64]) -> Result<()>

Initialize the sampler to a position. This should be called before calling draw.

fn draw(&mut self) -> Result<(Box<[f64]>, Progress)>

Draw a new sample and return the position and some diagnosic information.

fn dim(&self) -> usize

The dimensionality of the posterior.

fn expanded_draw( &mut self, ) -> Result<(Box<[f64]>, M::ExpandedVector, Self::Stats, Progress)>

fn math(&self) -> Ref<'_, M>

impl<M, R, A, T> SamplerStats<M> for MclmcChain<M, R, A, T>

where M: Math, R: Rng, T: Transformation<M>, A: AdaptStrategy<M, Hamiltonian = TransformedHamiltonian<M, T>>,

type Stats = MclmcStats<StatsDims, <TransformedHamiltonian<M, T> as SamplerStats<M>>::Stats, <A as SamplerStats<M>>::Stats, <TransformedPoint<M> as SamplerStats<M>>::Stats>

type StatsOptions = StatOptions<M, A>

fn extract_stats( &self, math: &mut M, options: Self::StatsOptions, ) -> Self::Stats