nuisance_e: Cross-fitted ensemble prediction of propensity score nuisance...
In MCKnaus/causalDML: Causal Double Machine Learning

nuisance_e

R Documentation

Cross-fitted ensemble prediction of propensity score nuisance parameter.

Cross-fitted ensemble prediction of propensity score nuisance parameter.

nuisance_e(ml, w_mat, x, cf_mat, cv = 5, path = NULL, quiet = TRUE)

`ml`	List of methods to be used in `ensemble` estimation of propensity score. Methods can be created by `create_method`.
`w_mat`	Logical matrix of treatment indicators (n x T+1). For example created by `prep_w_mat`.
`x`	Covariate matrix.
`cf_mat`	Logical matrix with k columns of indicators representing the different folds (for example created by `prep_cf_mat`).
`cv`	Number of cross-validation when estimating ensemble (default 5).
`path`	Optional path to save the `ensemble` objects for later inspection. Saved as Ensemble_Wi where i is the number of the treatment in multiple treatment settings.
`quiet`	If FALSE, ensemble estimators print method that is currently running.