est_dcar: DCAR Projection of the Efficient Influence Function

In haldensify: Highly Adaptive Lasso Conditional Density Estimation

DCAR Projection of the Efficient Influence Function

Description

DCAR Projection of the Efficient Influence Function

Usage

est_dcar(
  psi_ipw,
  gn_pred_natural,
  gn_pred_shifted,
  Qn_pred_natural,
  Qn_pred_shifted
)

Arguments

psi_ipw	A numeric vector of IPW point estimates corresponding to the conditional density estimates of the exposure mechanism provided in the arguments gn_pred_natural and gn_pred_shifted.
gn_pred_natural	A matrix of conditional density estimates of the exposure mechanism g(A|W) along a grid of the regularization parameter, at the natural (i.e., observed) values of the exposure.
gn_pred_shifted	A matrix of conditional density estimates of the exposure mechanism g(A+delta|W) along a grid of the regularization parameter, at the shifted (i.e., counterfactual) values of the exposure.
Qn_pred_natural	A numeric of the outcome mechanism estimate at the natural (i.e., observed) values of the exposure. HAL regression is used for the estimate, with the regularization term chosen by cross-validation.
Qn_pred_shifted	A numeric of the outcome mechanism estimate at the shifted (i.e., counterfactual) values of the exposure. HAL regression is used for the estimate, with the regularization term chosen by cross-validation.

haldensify documentation built on Sept. 2, 2025, 9:09 a.m.