Struct Qn 

pub struct Qn {
    pub consistency: f64,
    pub finite_sample_correction: bool,
}

Qn = c · dₙ · {|rᵢ − rⱼ| : i < j}₍ₖ₎, the k-th order statistic of the pairwise absolute differences with k = C(⌊n/2⌋+1, 2) (≈ the ¼-quantile). The constant c = 2.2219 = 1/(√2·Φ⁻¹(⅝)) gives consistency for σ at the Gaussian; dₙ is a finite-sample correction (Croux & Rousseeuw 1992).

Uses no location step and stays smooth in the data, with ≈ 82% Gaussian efficiency and a 50% breakdown point (versus the MAD’s ≈ 37%).

Evaluated directly over all pairs in O(n²) time / O(n²) space; Rousseeuw & Croux’s O(n log n) algorithm is a possible follow-up (the datasets here are small).

Fields

consistency: f64

Asymptotic consistency constant (default 2.2219).

finite_sample_correction: bool

Apply the finite-sample correction dₙ (default true).

Trait Implementations

impl Clone for Qn

fn clone(&self) -> Qn

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Copy for Qn

impl Debug for Qn

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

Formats the value using the given formatter.

impl Default for Qn

fn default() -> Qn

Returns the “default value” for a type.

impl ScaleEstimator for Qn

fn scale(&self, residuals: &[f64]) -> Result<Scale, RobustError>

A robust scale of the given residuals.