est_dcar: DCAR Projection of the Efficient Influence Function
In nhejazi/haldensify: Highly Adaptive Lasso Conditional Density Estimation

est_dcar

R Documentation

DCAR Projection of the Efficient Influence Function

DCAR Projection of the Efficient Influence Function

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

`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.