Struct Ols 

pub struct Ols { /* private fields */ }

Ordinary least squares with an intercept and optional ridge penalty.

ridge (default 0) is added to the diagonal for slopes only, which keeps the fit well defined when covariates are collinear.

Implementations

impl Ols

pub fn new() -> Self

pub fn with_ridge(ridge: f64) -> Self

pub fn coef(&self) -> Option<&Array1<f64>>

pub fn intercept(&self) -> f64

Trait Implementations

impl Clone for Ols

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Ols

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

Formats the value using the given formatter.

impl Default for Ols

fn default() -> Self

Returns the “default value” for a type.

impl Regressor for Ols

fn fit_weighted( &mut self, x: ArrayView2<'_, f64>, y: ArrayView1<'_, f64>, w: ArrayView1<'_, f64>, ) -> Result<()>

Weighted least squares: minimises Σ wᵢ (yᵢ − b − xᵢᵀβ)² + ridge·‖β‖².

fn fit(&mut self, x: ArrayView2<'_, f64>, y: ArrayView1<'_, f64>) -> Result<()>

fn predict(&self, x: ArrayView2<'_, f64>) -> Result<Array1<f64>>

fn fresh(&self) -> Box<dyn Regressor>