Struct ExpOverLinear 

pub struct ExpOverLinear;

Exponential decay divided by a line.

y = exp(−rate·x) / (lin_const + lin_slope·x)

Parameters (in order): [rate, lin_const, lin_slope]

This is the NIST StRD Chwirut model, shared by two datasets: Chwirut1 (214 observations) and Chwirut2 (54), which differ only in the data.

Domain guard: the denominator must be non-zero. Unlike a quadratic denominator this one has a single root at x = −lin_const/lin_slope, which a solver can walk onto during search even when the certified parameters keep it clear of the data, so D = 0 returns f64::NAN.

Analytic Jacobian (let E = exp(−rate·x), D = lin_const + lin_slope·x):

• ∂y/∂rate = −x·E / D
• ∂y/∂lin_const = −E / D²
• ∂y/∂lin_slope = −x·E / D²

Trait Implementations

impl Model for ExpOverLinear

fn eval(&self, x: &[f64], p: &[f64]) -> f64

Evaluate the model at coordinate x with the given params.

fn jacobian_into(&self, x: &[f64], p: &[f64], out: &mut [f64])

Fill a pre-allocated slice with Jacobian values (one entry per parameter).

fn jacobian(&self, x: &[f64], p: &[f64]) -> Vec<f64>

Jacobian — one derivative per parameter, in the same order as param_names().

fn param_names(&self) -> Vec<Cow<'static, str>>

Ordered parameter names, matching the layout expected by eval and jacobian.

fn eval_slice_into(&self, xs: &[f64], params: &[f64], out: &mut [f64])

Batch evaluation of a 1-D model: fill out[i] = eval([xs[i]], params).

fn jac_slice_into(&self, xs: &[f64], params: &[f64], out: &mut [f64])

Batch Jacobian for a 1-D model: fill out in row-major layout [i * params.len() + j] = d(model)/d(params[j]) at xs[i].

fn n_dims(&self) -> usize

Number of coordinate dimensions consumed from x. Defaults to 1.