Struct SkewedGaussian 

pub struct SkewedGaussian;

Skewed Gaussian: a Gaussian modulated by an error-function skew factor.

A · exp(−½((x−c)/σ)²) · (1 + erf(γ·(x−c)/(σ·√2)))

Parameters (in order): [amplitude, center, sigma, gamma]

• gamma is the skewness: 0 ⇒ symmetric Gaussian, γ>0 ⇒ tail toward high x, γ<0 ⇒ tail toward low x. Uses libm::erf.

Trait Implementations

impl Model for SkewedGaussian

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

Analytical Jacobian of the skewed Gaussian.

Let g = exp(−½(dx/σ)²), β = γ/(σ√2), skew = 1 + erf(β·dx), erf_d = (2/√π)·exp(−(β·dx)²) (the erf derivative factor).

∂f/∂A = g · skew ∂f/∂center = A·g · [ dx/σ² · skew − β · erf_d ] (∂dx/∂c = −1) ∂f/∂sigma = A·g · [ dx²/σ³ · skew − β·dx/σ · erf_d ] ∂f/∂gamma = A·g · [ dx/(σ√2) · erf_d ]

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

Evaluate the model at coordinate x with the given params.

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

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

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.