Enum NonParametricAlgorithm 

pub enum NonParametricAlgorithm {
    Npag(NpagConfig),
    Npod(NpodConfig),
    Npmap(NpmapConfig),
    Ncnpag(NcnpagConfig),
}

The non-parametric algorithms supported by PMcore.

Use the constructors to select an algorithm with its default configuration:

use pmcore::prelude::*;

// Default NPAG configuration.
let algorithm = NonParametricAlgorithm::npag();

To customize an algorithm, build its configuration struct (which exposes only the setters valid for that algorithm) and pass it directly to fit_with:

use pmcore::prelude::*;

// NPAG with a tighter convergence criterion and a cycle cap.
let config = NpagConfig::new().eps(0.1).max_cycles(500);
// `problem.fit_with(config)` accepts the config directly.

Each configuration type (NpagConfig, NpodConfig, NpmapConfig) implements Algorithm by delegating to the matching enum variant, so configs can be passed to fit_with without converting them first.

Variants

Npag(NpagConfig)

Non-Parametric Adaptive Grid.

Npod(NpodConfig)

Non-Parametric Optimal Design.

Npmap(NpmapConfig)

Non-parametric maximum a posteriori (posterior probability reweighting).

Ncnpag(NcnpagConfig)

Non-collapsing NPAG (single-pass Bayesian reweighting of fixed support points).

Implementations

impl NonParametricAlgorithm

pub fn npag() -> Self

The Non-Parametric Adaptive Grid (NPAG) algorithm with its default configuration.

pub fn npod() -> Self

The Non-Parametric Optimal Design (NPOD) algorithm with its default configuration.

pub fn npmap() -> Self

The non-parametric maximum a posteriori (NPMAP) algorithm with its default configuration.

pub fn ncnpag() -> Self

The non-collapsing NPAG (NCNPAG) algorithm with its default configuration.

Trait Implementations

impl<E: Equation + Send + 'static> Algorithm<E, NonParametric> for NonParametricAlgorithm

type Output = NonParametricResult<E>

The specific result struct (e.g. NonParametricResult<E>).

fn fit( self, problem: EstimationProblem<E, NonParametric>, ) -> Result<Self::Output>

Consumes the configuration and the problem, runs the optimization to completion, and returns the strictly-typed result.

impl Clone for NonParametricAlgorithm

fn clone(&self) -> NonParametricAlgorithm

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NonParametricAlgorithm

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

Formats the value using the given formatter.

impl Default for NonParametricAlgorithm

fn default() -> Self

Returns the “default value” for a type.

impl From<NcnpagConfig> for NonParametricAlgorithm

fn from(config: NcnpagConfig) -> Self

Converts to this type from the input type.

impl From<NpagConfig> for NonParametricAlgorithm

fn from(config: NpagConfig) -> Self

Converts to this type from the input type.

impl From<NpmapConfig> for NonParametricAlgorithm

fn from(config: NpmapConfig) -> Self

Converts to this type from the input type.

impl From<NpodConfig> for NonParametricAlgorithm

fn from(config: NpodConfig) -> Self

Converts to this type from the input type.