Struct Summary 

pub struct Summary {

    pub n_observations: usize,
    pub n_parameters: usize,
    pub df_residual: f64,
    pub has_intercept: bool,
    pub coefficients: Vec<CoefficientRow>,
    pub r_squared: f64,
    pub adj_r_squared: f64,
    pub f_statistic: FStatistic,
    pub residual_std_error: f64,
    pub log_likelihood: f64,
    pub aic: f64,
    pub bic: f64,
    pub condition_number: f64,
    pub durbin_watson: f64,
    pub jarque_bera: JarqueBera,
    pub breusch_pagan: BreuschPagan,
    pub white: WhiteTest,
}

A structured snapshot of every diagnostic in the crate for one fit.

Summary is structured data first: every field is a real number you can read programmatically. The Display impl is a convenience layer that renders it as a statsmodels-style table — it is not the primary interface, so you never have to parse text to get a value back out.

Build it with OlsFit::summary.

Fields

n_observations: usize

Number of observations.

n_parameters: usize

Number of parameters.

df_residual: f64

Residual degrees of freedom.

has_intercept: bool

Whether an intercept is present.

coefficients: Vec<CoefficientRow>

One row per coefficient.

r_squared: f64

R².

adj_r_squared: f64

Adjusted R².

f_statistic: FStatistic

Overall F-test.

residual_std_error: f64

Residual standard error s.

log_likelihood: f64

Gaussian log-likelihood.

aic: f64

Akaike information criterion.

bic: f64

Bayesian information criterion.

condition_number: f64

Design-matrix condition number.

durbin_watson: f64

Durbin-Watson statistic.

jarque_bera: JarqueBera

Jarque-Bera normality test.

breusch_pagan: BreuschPagan

Breusch-Pagan heteroskedasticity test.

white: WhiteTest

White’s heteroskedasticity test.

Implementations

impl Summary

pub fn max_cooks_distance(fit: &OlsFit) -> f64

Maximum absolute Cook’s distance across observations, recomputed from the fit — a convenience for callers that want a single influence headline number without walking the full vector. (Not stored on Summary because it is per-observation; use crate::influence::cooks_distance for the full vector.)

Trait Implementations

impl Clone for Summary

fn clone(&self) -> Summary

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Summary

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

Formats the value using the given formatter.

impl Display for Summary

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

Formats the value using the given formatter.