econml.inference.LinearModelFinalInference

class econml.inference.LinearModelFinalInference

Bases: econml.inference._inference.GenericModelFinalInference

Inference based on predict_interval of the model_final model. Assumes that estimator class has a model_final method and that model is linear. Thus, the predict(cross_product(X, T1 - T0)) gives the effect(X, T0, T1). This allows us to implement effect_interval(X, T0, T1) based on the predict_interval of model_final.

__init__()

Methods

__init__()
ate_inference([X, T0, T1])
ate_interval([X, T0, T1, alpha])
coef__inference()
coef__interval(*[, alpha])
const_marginal_ate_inference([X])
const_marginal_ate_interval([X, alpha])
const_marginal_effect_inference(X)
const_marginal_effect_interval(X, *[, alpha])
effect_inference(X, *, T0, T1)
effect_interval(X, *, T0, T1[, alpha])
fit(estimator, *args, **kwargs)	Fits the inference model.
intercept__inference()
intercept__interval(*[, alpha])
marginal_ate_inference(T[, X])
marginal_ate_interval(T[, X, alpha])
marginal_effect_inference(T, X)
marginal_effect_interval(T, X, *[, alpha])
prefit(estimator, *args, **kwargs)	Performs any necessary logic before the estimator's fit has been called.

fit(estimator, *args, **kwargs)

Fits the inference model.

This is called after the estimator’s fit.

prefit(estimator, *args, **kwargs)

Performs any necessary logic before the estimator’s fit has been called.