Partially Linear Regression DML on OTIS (not yet ported).

The python version uses scikit-learn RF nuisance models for the Frisch-Waugh-Lovell partialling-out construction. For the R port, use the analogous morie_estimate_double_ml() from causal.R, which already wraps DoubleML::DoubleMLPLR (with mlr3 ranger learners) and a cross-fit ridge fallback.

Usage

morie_otis_plr(...)

Arguments

...

Arguments mirroring morie_otis_aipw_ate().

Value

Stops with a redirect to morie_estimate_double_ml().

Examples

if (FALSE) { # \dontrun{
  morie_otis_plr(df, treatment = "d", outcome = "y",
                 covariates = "x")
} # }