Struct AverageDerivative 

pub struct AverageDerivative {
    pub step: Option<f64>,
}

Average derivative E[∂γ(D, X)/∂D] of a continuous treatment, by a central difference with step h (default 10⁻⁴ times the standard deviation of the treatment). Needs a regression that is smooth in the treatment (linear models, polynomials, neural networks); for trees use ShiftEffect.

Fields

step: Option<f64>

Implementations

impl AverageDerivative

pub fn new() -> Self

pub fn step(self, h: f64) -> Self

Trait Implementations

impl Clone for AverageDerivative

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Copy for AverageDerivative

impl Debug for AverageDerivative

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

Formats the value using the given formatter.

impl Default for AverageDerivative

fn default() -> Self

Returns the “default value” for a type.

impl LinearFunctional for AverageDerivative

fn name(&self) -> String

Label for summaries, e.g. "ATE".

fn terms(&self, w: ArrayView2<'_, f64>) -> Result<Vec<Term>>

The terms of m at the rows of w (all observations; w has the treatment in column 0 and the covariates after it).