Struct JackknifeResampling 

pub struct JackknifeResampling {
    pub scheme_name: String,
    pub description: String,
}

Leave-one-out resampling for bias and variance estimation.

Fields

scheme_name: String

Unique name identifying a resampling scheme.

description: String

Free-text description.

Implementations

impl JackknifeResampling

pub fn estimate( &self, data: &[f64], stat: impl Fn(&[f64]) -> f64, ) -> Result<JackknifeEstimate>

Computes the jackknife bias and standard error of stat over data.

Convenience wrapper that lets the JackknifeResampling scheme drive the numerics directly; it delegates to jackknife_statistic and shares its contract exactly.

Arguments

• data — the observed sample; must contain at least two values.
• stat — the statistic to jackknife, mapping a sample view to a scalar.

Returns

A JackknifeEstimate with the full-sample estimate, bias, standard error, and per-subsample replicates.

Errors

Returns Error::InsufficientData when data has fewer than two elements.

Examples

use stats_claw::resampling::JackknifeResampling;

let scheme = JackknifeResampling::default();
let data = [1.0, 2.0, 3.0, 4.0];
let est = scheme.estimate(&data, |s| s.iter().copied().fold(f64::MIN, f64::max))?;
assert!((est.estimate() - 4.0).abs() < 1e-12, "max was {}", est.estimate());

Trait Implementations

impl Clone for JackknifeResampling

fn clone(&self) -> JackknifeResampling

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for JackknifeResampling

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

Formats the value using the given formatter.

impl Default for JackknifeResampling

fn default() -> JackknifeResampling

Returns the “default value” for a type.