Trait AdvancedTarget 

pub trait AdvancedTarget<F>: Send + Sync
where
    F: Float + Copy + Display,
{
    // Required methods
    fn log_density(&self, x: &Array1<F>) -> F;
    fn gradient(&self, x: &Array1<F>) -> Array1<F>;
    fn dim(&self) -> usize;

    // Provided methods
    fn log_density_and_gradient(&self, x: &Array1<F>) -> (F, Array1<F>) { ... }
    fn hessian(x: &Array1<F>) -> Option<Array2<F>> { ... }
    fn fisher_information(x: &Array1<F>) -> Option<Array2<F>> { ... }
    fn riemann_metric(x: &Array1<F>) -> Option<Array2<F>> { ... }
    fn modeldimension(&self, modelid: usize) -> usize { ... }
    fn model_transition_prob(from_model: usize, _tomodel: usize) -> F { ... }
    fn batch_log_density(&self, xbatch: &Array2<F>) -> Array1<F> { ... }
}

Advanced-advanced target distribution interface

Required Methods

fn log_density(&self, x: &Array1<F>) -> F

Compute log probability density

fn gradient(&self, x: &Array1<F>) -> Array1<F>

Compute gradient of log density

fn dim(&self) -> usize

Get dimensionality

Provided Methods

fn log_density_and_gradient(&self, x: &Array1<F>) -> (F, Array1<F>)

Compute both log density and gradient efficiently

fn hessian(x: &Array1<F>) -> Option<Array2<F>>

Compute Hessian matrix (for manifold methods)

fn fisher_information(x: &Array1<F>) -> Option<Array2<F>>

Compute Fisher information matrix

fn riemann_metric(x: &Array1<F>) -> Option<Array2<F>>

Compute Riemann metric tensor (for Riemannian methods)

fn modeldimension(&self, modelid: usize) -> usize

Support for discontinuous model spaces (for Reversible Jump)

fn model_transition_prob(from_model: usize, _tomodel: usize) -> F

Model transition probability (for Reversible Jump)

fn batch_log_density(&self, xbatch: &Array2<F>) -> Array1<F>

Support parallel evaluation of multiple points

Dyn Compatibility

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementors