docs and imports

Author: vincentarelbundock

R/inferences.R

@@ -24,6 +24,7 @@
 #' + `rsample`: "perc" or "bca"
 #' + `simulation`: "perc" or "wald"
 #' @param data_train Data frame used to train/fit the model. If `NULL`, `marginaleffects` tries to extract the data from the original model object. Test data are inferred directly from the `newdata` supplied to the originating `marginaleffects` call (e.g., `predictions()`).
+#' @param data_test Data frame make out of sample prediction. Only used for conformal inference. If `NULL`, the data frame supplied to `newdata` in the original `marginaleffects` call is used.
 #' @param data_calib Data frame used for calibration in split conformal prediction.
 #' @param conformal_score String. Warning: The `type` argument in `predictions()` must generate predictions which are on the same scale as the outcome variable. Typically, this means that `type` must be "response" or "probs".
 #'   + "residual_abs" or "residual_sq" for regression tasks (numeric outcome)

R/inferences_conformal_quantile.R

@@ -70,7 +70,7 @@ conformal_quantile <- function(x, data_test, data_train, data_calib, conf_level
     # Step 2: Get quantile predictions on calibration set
     # Use same predictor columns in same order as training
     x_calib <- as.data.frame(data_calib)[, predictor_cols, drop = FALSE]
-    q_calib <- predict(qrf, newdata = x_calib, what = c(alpha / 2, 1 - alpha / 2))
+    q_calib <- stats::predict(qrf, newdata = x_calib, what = c(alpha / 2, 1 - alpha / 2))
     q_calib_low <- q_calib[, 1]
     q_calib_high <- q_calib[, 2]
 
@@ -96,7 +96,7 @@ conformal_quantile <- function(x, data_test, data_train, data_calib, conf_level
     # Step 5: Get quantile predictions on test set
     # Use same predictor columns in same order as training
     x_test <- as.data.frame(data_test)[, predictor_cols, drop = FALSE]
-    q_test <- predict(qrf, newdata = x_test, what = c(alpha / 2, 1 - alpha / 2))
+    q_test <- stats::predict(qrf, newdata = x_test, what = c(alpha / 2, 1 - alpha / 2))
     q_test_low <- q_test[, 1]
     q_test_high <- q_test[, 2]