diff --git a/R/aoa.R b/R/aoa.R
index dda3010f..ac2482e1 100644
--- a/R/aoa.R
+++ b/R/aoa.R
@@ -26,7 +26,7 @@
 #' Relevant if some data points are excluded, e.g. when using \code{\link{nndm}}.
 #' @param method Character. Method used for distance calculation. Currently euclidean distance (L2) and Mahalanobis distance (MD) are implemented but only L2 is tested. Note that MD takes considerably longer.
 #' @param useWeight Logical. Only if a model is given. Weight variables according to importance in the model?
-#' @param LPD Logical. Indicates weather the local point density should be calculated or not.
+#' @param LPD Logical. Indicates whether the local point density should be calculated or not.
 #' @param maxLPD numeric or integer. Only if \code{LPD = TRUE}. Number of nearest neighbors to be considered for the calculation of the LPD. Either define a number between 0 and 1 to use a percentage of the number of training samples for the LPD calculation or a whole number larger than 1 and smaller than the number of training samples. CAUTION! If not all training samples are considered, a fitted relationship between LPD and error metric will not make sense (@seealso \code{\link{DItoErrormetric}})
 #' @details The Dissimilarity Index (DI), the Local Data Point Density (LPD) and the corresponding Area of Applicability (AOA) are calculated.
 #' If variables are factors, dummy variables are created prior to weighting and distance calculation.
diff --git a/R/trainDI.R b/R/trainDI.R
index fc456a05..ae8bc2b8 100644
--- a/R/trainDI.R
+++ b/R/trainDI.R
@@ -23,7 +23,7 @@
 #' Relevant if some data points are excluded, e.g. when using \code{\link{nndm}}.
 #' @param method Character. Method used for distance calculation. Currently euclidean distance (L2) and Mahalanobis distance (MD) are implemented but only L2 is tested. Note that MD takes considerably longer.
 #' @param useWeight Logical. Only if a model is given. Weight variables according to importance in the model?
-#' @param LPD Logical. Indicates wheather the local point density should be calculated or not.
+#' @param LPD Logical. Indicates whether the local point density should be calculated or not.
 #'
 #' @seealso \code{\link{aoa}}
 #' @importFrom graphics boxplot
diff --git a/man/aoa.Rd b/man/aoa.Rd
index b518b56e..49c2b5b1 100644
--- a/man/aoa.Rd
+++ b/man/aoa.Rd
@@ -47,7 +47,7 @@ Relevant if some data points are excluded, e.g. when using \code{\link{nndm}}.}
 
 \item{useWeight}{Logical. Only if a model is given. Weight variables according to importance in the model?}
 
-\item{LPD}{Logical. Indicates weather the local point density should be calculated or not.}
+\item{LPD}{Logical. Indicates whether the local point density should be calculated or not.}
 
 \item{maxLPD}{numeric or integer. Only if \code{LPD = TRUE}. Number of nearest neighbors to be considered for the calculation of the LPD. Either define a number between 0 and 1 to use a percentage of the number of training samples for the LPD calculation or a whole number larger than 1 and smaller than the number of training samples. CAUTION! If not all training samples are considered, a fitted relationship between LPD and error metric will not make sense (@seealso \code{\link{DItoErrormetric}})}
 }
diff --git a/man/trainDI.Rd b/man/trainDI.Rd
index 7ec6f655..aaac35e0 100644
--- a/man/trainDI.Rd
+++ b/man/trainDI.Rd
@@ -38,7 +38,7 @@ Relevant if some data points are excluded, e.g. when using \code{\link{nndm}}.}
 
 \item{useWeight}{Logical. Only if a model is given. Weight variables according to importance in the model?}
 
-\item{LPD}{Logical. Indicates wheather the local point density should be calculated or not.}
+\item{LPD}{Logical. Indicates whether the local point density should be calculated or not.}
 }
 \value{
 A list of class \code{trainDI} containing: