`shrinkage::NullModelDatafit`

Shrinkage for Rust · rust · 0.3.0

Source: src/path/datafit.rs

pub trait NullModelDatafit

An exact zero-coefficient model with optimized, unpenalized intercepts.

This opt-in capability is independent of fitting arbitrary explicit paths.

Methods

`deviance`

Source: src/path/datafit.rs

fn deviance(&self, _predictor: &[f64]) -> Result<Option<f64>, FitError>

Evaluate twice the loss above its saturated value, averaged over rows. Return None when deviance is unavailable; automatic paths then fit their entire sequence. Support must be consistent across predictors.

Errors

Reject invalid responses, predictors, or nonfinite arithmetic.

`null_intercepts`

Source: src/path/datafit.rs

fn null_intercepts(&self) -> Result<Vec<f64>, FitError>

Return one finite optimization-scale intercept per response, or zero for each disabled intercept. Validate the response before returning.

Errors

Reject invalid responses or a null model without a finite optimum.

Implementation of NullModelDatafit

Source: src/path/datafit.rs

impl NullModelDatafit for shrinkage::Binomial<'_>

Implementation of NullModelDatafit

Source: src/path/datafit.rs

impl NullModelDatafit for shrinkage::Gaussian<'_>

Implementation of NullModelDatafit

Source: src/path/datafit.rs

impl NullModelDatafit for shrinkage::MultivariateGaussian<'_>

Implementation of NullModelDatafit

Source: src/datafit/linked.rs

impl<'a, L: ConvexLink<shrinkage::Binomial<'a>>> NullModelDatafit for LinkedDatafit<shrinkage::Binomial<'a>, L>

Implementation of NullModelDatafit

Source: src/datafit/linked.rs

impl<'a, L: ConvexLink<shrinkage::Gaussian<'a>>> NullModelDatafit for LinkedDatafit<shrinkage::Gaussian<'a>, L>