diff --git a/R/create_LDprofile.R b/R/create_LDprofile.R
index c89fc356cc0d91fde6dca7df2873c7237bf2b4c0..331bf49d265e226675a78e228ed80b5906ed6c00 100644
--- a/R/create_LDprofile.R
+++ b/R/create_LDprofile.R
@@ -10,6 +10,8 @@
 #' If the \code{max_dist} is not an increment of \code{bin_size}, it will be adjusted to the next highest increment. The final bin will be the bin that \code{max_dist} falls into. For example, if the \code{max_dist} is given as 4.5 and the \code{bin_size} is 1, the final bin will be 4.\cr
 #' By default, Beta parameters are not calculated. To fit a Beta distribution to the expected correlations, needed for the \code{\link{Zalpha_BetaCDF}} and \code{\link{Zbeta_BetaCDF}} statistics, \code{beta_params} should be set to TRUE and the package 'fitdistrplus' must be installed.
 #'
+#' Ideally, an LD profile would be generated using data from a null population with no selection, For example by using a simulation if the other population parameters are known. However, often these are unknown or complex, so generating an LD profile using the same data as is being analysed is acceptable, as long as the bins are large enough.
+#'
 #' @importFrom stats cor sd
 #'
 #' @param dist A numeric vector, or a list of numeric vectors, containing the genetic distance for each SNP.
@@ -32,7 +34,7 @@
 #'
 #'
 #' @export
-#' @seealso \code{\link{Zalpha_expected}} \code{\link{Zalpha_rsq_over_expected}} \code{\link{Zalpha_log_rsq_over_expected}} \code{\link{Zalpha_Zscore}} \code{\link{Zalpha_BetaCDF}} \code{\link{Zbeta_expected}} \code{\link{Zbeta_rsq_over_expected}} \code{\link{Zbeta_log_rsq_over_expected}} \code{\link{Zbeta_Zscore}} \code{\link{Zbeta_BetaCDF}} \code{\link{Zalpha_all}}
+#' @seealso \code{\link{Zalpha_expected}}, \code{\link{Zalpha_rsq_over_expected}}, \code{\link{Zalpha_log_rsq_over_expected}}, \code{\link{Zalpha_Zscore}}, \code{\link{Zalpha_BetaCDF}}, \code{\link{Zbeta_expected}}, \code{\link{Zbeta_rsq_over_expected}}, \code{\link{Zbeta_log_rsq_over_expected}}, \code{\link{Zbeta_Zscore}}, \code{\link{Zbeta_BetaCDF}}, \code{\link{Zalpha_all}}.
 #'
 create_LDprofile<-function(dist,x,bin_size,max_dist=NULL,beta_params=FALSE){
 
diff --git a/man/create_LDprofile.Rd b/man/create_LDprofile.Rd
index 15e3d5218f0aba8195ba5530574644dca37eddd7..b5d70a487b878cd5c1a43e0ea5cd76c8cc31f36c 100644
--- a/man/create_LDprofile.Rd
+++ b/man/create_LDprofile.Rd
@@ -30,6 +30,8 @@ Both lists should be the same length and should correspond exactly to each other
 In the output, bins represent lower bounds. The first bin contains pairs where the genetic distance is greater than or equal to 0 and less than \code{bin_size}. The final bin contains pairs where the genetic distance is greater than or equal to \code{max_dist}-\code{bin_size} and less than \code{max_dist}.
 If the \code{max_dist} is not an increment of \code{bin_size}, it will be adjusted to the next highest increment. The final bin will be the bin that \code{max_dist} falls into. For example, if the \code{max_dist} is given as 4.5 and the \code{bin_size} is 1, the final bin will be 4.\cr
 By default, Beta parameters are not calculated. To fit a Beta distribution to the expected correlations, needed for the \code{\link{Zalpha_BetaCDF}} and \code{\link{Zbeta_BetaCDF}} statistics, \code{beta_params} should be set to TRUE and the package 'fitdistrplus' must be installed.
+
+Ideally, an LD profile would be generated using data from a null population with no selection, For example by using a simulation if the other population parameters are known. However, often these are unknown or complex, so generating an LD profile using the same data as is being analysed is acceptable, as long as the bins are large enough.
 }
 \examples{
 ## load the snps example dataset
@@ -47,5 +49,5 @@ if (requireNamespace("fitdistrplus", quietly = TRUE)==TRUE) {
 Jacobs, G.S., T.J. Sluckin, and T. Kivisild, \emph{Refining the Use of Linkage Disequilibrium as a Robust Signature of Selective Sweeps.} Genetics, 2016. \strong{203}(4): p. 1807
 }
 \seealso{
-\code{\link{Zalpha_expected}} \code{\link{Zalpha_rsq_over_expected}} \code{\link{Zalpha_log_rsq_over_expected}} \code{\link{Zalpha_Zscore}} \code{\link{Zalpha_BetaCDF}} \code{\link{Zbeta_expected}} \code{\link{Zbeta_rsq_over_expected}} \code{\link{Zbeta_log_rsq_over_expected}} \code{\link{Zbeta_Zscore}} \code{\link{Zbeta_BetaCDF}} \code{\link{Zalpha_all}}
+\code{\link{Zalpha_expected}}, \code{\link{Zalpha_rsq_over_expected}}, \code{\link{Zalpha_log_rsq_over_expected}}, \code{\link{Zalpha_Zscore}}, \code{\link{Zalpha_BetaCDF}}, \code{\link{Zbeta_expected}}, \code{\link{Zbeta_rsq_over_expected}}, \code{\link{Zbeta_log_rsq_over_expected}}, \code{\link{Zbeta_Zscore}}, \code{\link{Zbeta_BetaCDF}}, \code{\link{Zalpha_all}}.
 }