diff --git a/R/meta_learner.R b/R/meta_learner.R
index e2acf970..40204d43 100644
--- a/R/meta_learner.R
+++ b/R/meta_learner.R
@@ -2,7 +2,7 @@
 #' Fit our meta learner. It takes predictions of other models such as
 #' kriging, GLM, machine learning models as input and fits a new model
 #' @param base_predictor_list - a list where each
-#' @param meta_learner_obj
+#' @param meta_learner_obj an exported S3/S4/function that is the meta learner
 #' @param train_loc sf geospatial information on training locations
 #' @param kfolds integer, index of k-folds for cross-validation. This should be
 #' produced with regards to spatial and/or temporal considerations
@@ -22,8 +22,8 @@ meta_learner_fit <- function(base_predictor_list, meta_learner_obj,
 #' meta_learner_predict - take the meta_fit_obj and prediction location info
 #' to create meta_learner predictions
 #'
-#' @param meta_fit_obj
-#' @param pred_grid
+#' @param meta_fit_obj S3/S4 object from meta_learner_fit
+#' @param pred_grid sf or dataframe grid of prediction locations
 #' @return meta_pred_nc NetCDF (nc) file of the final meta learner predictions
 #' @export
 #'
diff --git a/man/meta_learner_fit.Rd b/man/meta_learner_fit.Rd
index baf8bc7e..eb8e92fc 100644
--- a/man/meta_learner_fit.Rd
+++ b/man/meta_learner_fit.Rd
@@ -11,6 +11,8 @@ meta_learner_fit(base_predictor_list, meta_learner_obj, train_loc, kfolds)
 \arguments{
 \item{base_predictor_list}{- a list where each}
 
+\item{meta_learner_obj}{an exported S3/S4/function that is the meta learner}
+
 \item{train_loc}{sf geospatial information on training locations}
 
 \item{kfolds}{integer, index of k-folds for cross-validation. This should be
diff --git a/man/meta_learner_predict.Rd b/man/meta_learner_predict.Rd
index 25de2214..a878459a 100644
--- a/man/meta_learner_predict.Rd
+++ b/man/meta_learner_predict.Rd
@@ -7,6 +7,11 @@ to create meta_learner predictions}
 \usage{
 meta_learner_predict(meta_fit_obj, pred_loc)
 }
+\arguments{
+\item{meta_fit_obj}{S3/S4 object from meta_learner_fit}
+
+\item{pred_grid}{sf or dataframe grid of prediction locations}
+}
 \value{
 meta_pred_nc NetCDF (nc) file of the final meta learner predictions
 }