fix problems after resolving merge conflicts

Author: MalteKurz

R/double_ml_pliv.R

@@ -542,7 +542,8 @@ DoubleMLPLIV = R6Class("DoubleMLPLIV",
           fold_specific_params = private$fold_specific_params)
       }
 
-      res = private$score_elements(y, z, d, l_hat, m_hat, r_hat, g_hat, smpls)
+      res = private$score_elements(y, z, d, l_hat$preds, m_hat$preds,
+                                   r_hat$preds, g_hat$preds, smpls)
       res$preds = list(
         "ml_l" = l_hat$preds,
         "ml_m" = m_hat$preds,

R/double_ml_plr.R

@@ -409,8 +409,8 @@ DoubleMLPLR = R6Class("DoubleMLPLR",
       g_hat = list(preds = NULL, models = NULL)
       if (exists("ml_g", where = private$learner_)) {
         # get an initial estimate for theta using the partialling out score
-        psi_a = -(d - m_hat) * (d - m_hat)
-        psi_b = (d - m_hat) * (y - l_hat)
+        psi_a = -(d - m_hat$preds) * (d - m_hat$preds)
+        psi_b = (d - m_hat$preds) * (y - l_hat$preds)
         theta_initial = -mean(psi_b, na.rm = TRUE) / mean(psi_a, na.rm = TRUE)
 
         data_aux = data.table(self$data$data_model,
@@ -428,7 +428,8 @@ DoubleMLPLR = R6Class("DoubleMLPLR",
           fold_specific_params = private$fold_specific_params)
       }
 
-      res = private$score_elements(y, d, l_hat, m_hat, g_hat, smpls)
+      res = private$score_elements(y, d, l_hat$preds, m_hat$preds, g_hat$preds,
+                                   smpls)
       res$preds = list(
         "ml_l" = l_hat$preds,
         "ml_m" = m_hat$preds,