From 6fa7aab9cba87d94a475e59a3058dabb8f4fed37 Mon Sep 17 00:00:00 2001
From: chorscroft <c.horscroft@soton.ac.uk>
Date: Wed, 26 Feb 2020 17:50:33 +0000
Subject: [PATCH] Fixed typos and grammar

---
 R/LDprofile-data.R                  | 6 +++---
 R/LR.R                              | 2 +-
 R/L_plus_R.R                        | 2 +-
 R/Zalpha_BetaCDF.R                  | 8 ++++----
 R/Zalpha_Zscore.R                   | 8 ++++----
 R/Zalpha_all.R                      | 4 ++--
 R/Zalpha_expected.R                 | 6 +++---
 R/Zalpha_log_rsq_over_expected.R    | 8 ++++----
 R/Zalpha_rsq_over_expected.R        | 8 ++++----
 R/Zbeta.R                           | 4 ++--
 R/Zbeta_BetaCDF.R                   | 8 ++++----
 R/Zbeta_Zscore.R                    | 8 ++++----
 R/Zbeta_expected.R                  | 6 +++---
 R/Zbeta_log_rsq_over_expected.R     | 8 ++++----
 R/Zbeta_rsq_over_expected.R         | 8 ++++----
 R/zalpha.R                          | 4 ++--
 man/LDprofile.Rd                    | 6 +++---
 man/LR.Rd                           | 2 +-
 man/L_plus_R.Rd                     | 2 +-
 man/Zalpha_BetaCDF.Rd               | 8 ++++----
 man/Zalpha_Zscore.Rd                | 8 ++++----
 man/Zalpha_all.Rd                   | 4 ++--
 man/Zalpha_expected.Rd              | 6 +++---
 man/Zalpha_log_rsq_over_expected.Rd | 8 ++++----
 man/Zalpha_rsq_over_expected.Rd     | 8 ++++----
 man/Zbeta.Rd                        | 4 ++--
 man/Zbeta_BetaCDF.Rd                | 8 ++++----
 man/Zbeta_Zscore.Rd                 | 8 ++++----
 man/Zbeta_expected.Rd               | 6 +++---
 man/Zbeta_log_rsq_over_expected.Rd  | 8 ++++----
 man/Zbeta_rsq_over_expected.Rd      | 8 ++++----
 man/zalpha.Rd                       | 4 ++--
 32 files changed, 98 insertions(+), 98 deletions(-)

diff --git a/R/LDprofile-data.R b/R/LDprofile-data.R
index 25f1e0d..8b8e869 100644
--- a/R/LDprofile-data.R
+++ b/R/LDprofile-data.R
@@ -1,6 +1,6 @@
 #' Dataset containing an example LD profile
 #'
-#' A simulated LD profile, containing example LD statisics for
+#' A simulated LD profile, containing example LD statistics for
 #' genetic distances of 0 to 0.0049, in bins of size 0.0001.
 #'
 #' @docType data
@@ -10,8 +10,8 @@
 #' @format A data frame with 50 rows and 5 variables:
 #' \describe{
 #'   \item{bin}{the lower bound of each bin}
-#'   \item{rsq}{the expected rsq value for a pair of snps, where the genetic distance between them falls in the given bin}
-#'   \item{sd}{the standard deviation of the expected rsq value}
+#'   \item{rsq}{the expected \eqn{r^2}{r^2} value for a pair of SNPs, where the genetic distance between them falls in the given bin}
+#'   \item{sd}{the standard deviation of the expected \eqn{r^2}{r^2} value}
 #'   \item{Beta_a}{the first shape parameter for the Beta distribution fitted for this bin}
 #'   \item{Beta_b}{the second shape parameter for the Beta distribution fitted for this bin}
 #' }
diff --git a/R/LR.R b/R/LR.R
index a1ef827..7c437ee 100644
--- a/R/LR.R
+++ b/R/LR.R
@@ -2,7 +2,7 @@
 #' Runs the LR function
 #'
 #' Returns the \code{|L||R|} value for each SNP location supplied to the function.
-#' For more information about the \code{|L||R|} diversity statistic please see Jacobs (2016).
+#' For more information about the \code{|L||R|} diversity statistic, please see Jacobs (2016).
 #'
 #' @param pos A numeric vector of SNP locations
 #' @param ws The window size which the \code{LR} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
diff --git a/R/L_plus_R.R b/R/L_plus_R.R
index 44425d3..5bb83ef 100644
--- a/R/L_plus_R.R
+++ b/R/L_plus_R.R
@@ -2,7 +2,7 @@
 #' Runs the L_plus_R function
 #'
 #' Returns the \eqn{{|L| \choose 2} + {|R| \choose 2}}{(|L| choose 2) + (|R| choose 2)} value for each SNP location supplied to the function.
-#' For more information about the \code{L_plus_R} diversity statistic please see Jacobs (2016).
+#' For more information about the \code{L_plus_R} diversity statistic, please see Jacobs (2016).
 #'
 #'
 #'
diff --git a/R/Zalpha_BetaCDF.R b/R/Zalpha_BetaCDF.R
index f07cf3f..35e37d6 100644
--- a/R/Zalpha_BetaCDF.R
+++ b/R/Zalpha_BetaCDF.R
@@ -4,7 +4,7 @@
 #'
 #' Returns a \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} statistic is defined as:
 #' \deqn{{Z_{\alpha}^{BetaCDF}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}\frac{B(r^2_{i,j};a,b)}{B(a,b)} + {|R| \choose 2}^{-1}\sum_{i,j \in R}\frac{B(r^2_{i,j};a,b)}{B(a,b)}}{2}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -12,14 +12,14 @@
 #' the estimated a and b parameters from the LD profile.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @importFrom stats cor pbeta
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param dist A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.
 #' @param ws The window size which the \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param LDprofile_bins A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size.
diff --git a/R/Zalpha_Zscore.R b/R/Zalpha_Zscore.R
index 65977b0..43f738f 100644
--- a/R/Zalpha_Zscore.R
+++ b/R/Zalpha_Zscore.R
@@ -4,21 +4,21 @@
 #'
 #' Returns a \eqn{Z_{\alpha}^{Zscore}}{Zalpha} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\alpha}^{Zscore}}{Zalpha} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\alpha}^{Zscore}}{Zalpha} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\alpha}^{Zscore}}{Zalpha} statistic is defined as:
 #' \deqn{{Z_{\alpha}^{Zscore}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}\frac{r^2_{i,j}-E[r^2_{i,j}]}{\sigma[r^2_{i,j}]} + {|R| \choose 2}^{-1}\sum_{i,j \in R}\frac{r^2_{i,j}-E[r^2_{i,j}]}{\sigma[r^2_{i,j}]}}{2}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
 #' the squared correlation between a pair of SNPs, \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a pair of SNPs, given an LD profile, and \eqn{\sigma[r^2]}{\sigma[r^2]} is the standard deviation.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @importFrom stats cor
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param dist A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.
 #' @param ws The window size which the \eqn{Z_{\alpha}^{Zscore}}{Zalpha} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param LDprofile_bins A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size.
diff --git a/R/Zalpha_all.R b/R/Zalpha_all.R
index eed6e3c..2ec094f 100644
--- a/R/Zalpha_all.R
+++ b/R/Zalpha_all.R
@@ -11,12 +11,12 @@
 #'   \item For \code{\link{Zalpha_Zscore}} and \code{\link{Zbeta_Zscore}} to be calculated, the parameter \code{LDprofile_sd} must also be supplied.
 #'   \item For \code{\link{Zalpha_BetaCDF}} and \code{\link{Zbeta_BetaCDF}} to be calculated, the parameters \code{LDprofile_Beta_a} and \code{LDprofile_Beta_b} must also be supplied.
 #' }
-#' For more information about the statistics please see Jacobs (2016).
+#' For more information about the statistics, please see Jacobs (2016).
 #'
 #' @importFrom stats cor pbeta
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x Optional. A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x Optional. A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param ws The window size which the statistics will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param dist Optional. A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.
 #' @param LDprofile_bins Optional. A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size.
diff --git a/R/Zalpha_expected.R b/R/Zalpha_expected.R
index 108d966..cc97349 100644
--- a/R/Zalpha_expected.R
+++ b/R/Zalpha_expected.R
@@ -4,15 +4,15 @@
 #'
 #' Returns a \eqn{Z_{\alpha}^{E[r^2]}}{Zalpha} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\alpha}^{E[r^2]}}{Zalpha} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\alpha}^{E[r^2]}}{Zalpha} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\alpha}^{E[r^2]}} statistic is defined as:
 #' \deqn{{Z_{\alpha}^{E[r^2]}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}E[r^2_{i,j}] + {|R| \choose 2}^{-1}\sum_{i,j \in R}E[r^2_{i,j}]}{2}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws},
 #' and \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a pair of SNPs, given an LD profile.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @param pos A numeric vector of SNP locations
diff --git a/R/Zalpha_log_rsq_over_expected.R b/R/Zalpha_log_rsq_over_expected.R
index 643bc95..608860a 100644
--- a/R/Zalpha_log_rsq_over_expected.R
+++ b/R/Zalpha_log_rsq_over_expected.R
@@ -4,21 +4,21 @@
 #'
 #' Returns a \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}{Zalpha} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}{Zalpha} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}{Zalpha} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}{Zalpha} statistic is defined as:
 #' \deqn{{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}log_{10}(r^2_{i,j}/E[r^2_{i,j}]) + {|R| \choose 2}^{-1}\sum_{i,j \in R}log_{10}(r^2_{i,j}/E[r^2_{i,j}])}{2}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
 #' the squared correlation between a pair of SNPs, and \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a pair of SNPs, given an LD profile.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @importFrom stats cor
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param dist A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.
 #' @param ws The window size which the \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}{Zalpha} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param LDprofile_bins A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size.
diff --git a/R/Zalpha_rsq_over_expected.R b/R/Zalpha_rsq_over_expected.R
index baf6f30..4f2f28c 100644
--- a/R/Zalpha_rsq_over_expected.R
+++ b/R/Zalpha_rsq_over_expected.R
@@ -4,21 +4,21 @@
 #'
 #' Returns a \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha} statistic is defined as:
 #' \deqn{{Z_{\alpha}^{r^2/E[r^2]}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}r^2_{i,j}/E[r^2_{i,j}] + {|R| \choose 2}^{-1}\sum_{i,j \in R}r^2_{i,j}/E[r^2_{i,j}]}{2}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
 #' the squared correlation between a pair of SNPs, and \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a pair of SNPs, given an LD profile.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @importFrom stats cor
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param dist A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.
 #' @param ws The window size which the \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param LDprofile_bins A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size.
diff --git a/R/Zbeta.R b/R/Zbeta.R
index 8470364..cfd8593 100644
--- a/R/Zbeta.R
+++ b/R/Zbeta.R
@@ -2,7 +2,7 @@
 #' Runs the Zbeta function
 #'
 #' Returns a \eqn{Z_{\beta}}{Zbeta} value for each SNP location supplied to the function.
-#' For more information about the \eqn{Z_{\beta}}{Zbeta} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\beta}}{Zbeta} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\beta}}{Zbeta} statistic is defined as:
 #' \deqn{Z_{\beta}=\frac{\sum_{i \in L,j \in R}r^2_{i,j}}{|L||R|}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, and \eqn{r^2}{r^2} is equal to the squared correlation between a pair of SNPs
@@ -10,7 +10,7 @@
 #' @importFrom stats cor
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param ws The window size which the \eqn{Z_{\beta}}{Zbeta} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param minRandL Minimum number of SNPs in each set R and L for the statistic to be calculated. Default is 4.
 #' @param minRL Minimum value for the product of the set sizes for R and L. Default is 25.
diff --git a/R/Zbeta_BetaCDF.R b/R/Zbeta_BetaCDF.R
index 958b74d..fa09a27 100644
--- a/R/Zbeta_BetaCDF.R
+++ b/R/Zbeta_BetaCDF.R
@@ -4,7 +4,7 @@
 #'
 #' Returns a \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} statistic is defined as:
 #' \deqn{Z_{\beta}^{BetaCDF}=\frac{\sum_{i \in L,j \in R}\frac{B(r^2_{i,j};a,b)}{B(a,b)}}{|L||R|}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -12,14 +12,14 @@
 #' the estimated a and b parameters from the LD profile.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @importFrom stats cor pbeta
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param dist A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.
 #' @param ws The window size which the \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param LDprofile_bins A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size.
diff --git a/R/Zbeta_Zscore.R b/R/Zbeta_Zscore.R
index b386747..82e3978 100644
--- a/R/Zbeta_Zscore.R
+++ b/R/Zbeta_Zscore.R
@@ -4,21 +4,21 @@
 #'
 #' Returns a \eqn{Z_{\beta}^{Zscore}}{Zbeta} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\beta}^{Zscore}}{Zbeta} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\beta}^{Zscore}}{Zbeta} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\beta}^{Zscore}}{Zbeta} statistic is defined as:
 #' \deqn{Z_{\beta}^{Zscore}=\frac{\sum_{i \in L,j \in R}\frac{r^2_{i,j}-E[r^2_{i,j}]}{\sigma[r^2_{i,j}]}}{|L||R|}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
 #' the squared correlation between a pair of SNPs, \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a pair of SNPs, given an LD profile, and \eqn{\sigma[r^2]}{\sigma[r^2]} is the standard deviation.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @importFrom stats cor
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param dist A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.
 #' @param ws The window size which the \eqn{Z_{\beta}^{Zscore}}{Zbeta} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param LDprofile_bins A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size.
diff --git a/R/Zbeta_expected.R b/R/Zbeta_expected.R
index e4a1332..9b8f250 100644
--- a/R/Zbeta_expected.R
+++ b/R/Zbeta_expected.R
@@ -4,15 +4,15 @@
 #'
 #' Returns a \eqn{Z_{\beta}^{E[r^2]}}{Zbeta} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\beta}^{E[r^2]}}{Zbeta} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\beta}^{E[r^2]}}{Zbeta} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\beta}^{E[r^2]}}{Zbeta} statistic is defined as:
 #' \deqn{Z_{\beta}^{E[r^2]}=\frac{\sum_{i \in L,j \in R}E[r^2_{i,j}]}{|L||R|}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws},
 #' and \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a pair of SNPs, given an LD profile.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @param pos A numeric vector of SNP locations
diff --git a/R/Zbeta_log_rsq_over_expected.R b/R/Zbeta_log_rsq_over_expected.R
index 2ad4b87..238df9d 100644
--- a/R/Zbeta_log_rsq_over_expected.R
+++ b/R/Zbeta_log_rsq_over_expected.R
@@ -4,21 +4,21 @@
 #'
 #' Returns a \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}}{Zbeta} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}}{Zbeta} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}}{Zbeta} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}}{Zbeta} statistic is defined as:
 #' \deqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}=\frac{\sum_{i \in L,j \in R}log_{10}(r^2_{i,j}/E[r^2_{i,j}])}{|L||R|}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
 #' the squared correlation between a pair of SNPs, and \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a pair of SNPs, given an LD profile.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @importFrom stats cor
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param dist A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.
 #' @param ws The window size which the \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}}{Zbeta} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param LDprofile_bins A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size.
diff --git a/R/Zbeta_rsq_over_expected.R b/R/Zbeta_rsq_over_expected.R
index 5afa73e..2fe6cbb 100644
--- a/R/Zbeta_rsq_over_expected.R
+++ b/R/Zbeta_rsq_over_expected.R
@@ -4,21 +4,21 @@
 #'
 #' Returns a \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta} value for each SNP location supplied to the function, based on
 #' the expected \eqn{r^2} values given an LD profile and genetic distances.
-#' For more information about the \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta} statistic is defined as:
 #' \deqn{Z_{\beta}^{r^2/E[r^2]}=\frac{\sum_{i \in L,j \in R}r^2_{i,j}/E[r^2_{i,j}]}{|L||R|}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
 #' the squared correlation between a pair of SNPs, and \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a pair of SNPs, given an LD profile.
 #'
 #' The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-#' real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-#' profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+#' real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+#' profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 #' bound of the bin.
 #'
 #' @importFrom stats cor
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param dist A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.
 #' @param ws The window size which the \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param LDprofile_bins A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size.
diff --git a/R/zalpha.R b/R/zalpha.R
index d744760..7414560 100644
--- a/R/zalpha.R
+++ b/R/zalpha.R
@@ -2,7 +2,7 @@
 #' Runs the Zalpha function
 #'
 #' Returns a \eqn{Z_{\alpha}}{Zalpha} value for each SNP location supplied to the function.
-#' For more information about the \eqn{Z_{\alpha}}{Zalpha} statistic please see Jacobs (2016).
+#' For more information about the \eqn{Z_{\alpha}}{Zalpha} statistic, please see Jacobs (2016).
 #' The \eqn{Z_{\alpha}}{Zalpha} statistic is defined as:
 #' \deqn{Z_{\alpha}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}r^2_{i,j} + {|R| \choose 2}^{-1}\sum_{i,j \in L}r^2_{i,j}}{2}}
 #' where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, and \eqn{r^2}{r^2} is equal to the squared correlation between a pair of SNPs
@@ -10,7 +10,7 @@
 #' @importFrom stats cor
 #'
 #' @param pos A numeric vector of SNP locations
-#' @param x A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
+#' @param x A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.
 #' @param ws The window size which the \eqn{Z_{\alpha}}{Zalpha} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.
 #' @param minRandL Minimum number of SNPs in each set R and L for the statistic to be calculated. Default is 4.
 #' @param minRL Minimum value for the product of the set sizes for R and L. Default is 25.
diff --git a/man/LDprofile.Rd b/man/LDprofile.Rd
index b3c23d9..a0ee7da 100644
--- a/man/LDprofile.Rd
+++ b/man/LDprofile.Rd
@@ -7,8 +7,8 @@
 \format{A data frame with 50 rows and 5 variables:
 \describe{
   \item{bin}{the lower bound of each bin}
-  \item{rsq}{the expected rsq value for a pair of snps, where the genetic distance between them falls in the given bin}
-  \item{sd}{the standard deviation of the expected rsq value}
+  \item{rsq}{the expected \eqn{r^2}{r^2} value for a pair of SNPs, where the genetic distance between them falls in the given bin}
+  \item{sd}{the standard deviation of the expected \eqn{r^2}{r^2} value}
   \item{Beta_a}{the first shape parameter for the Beta distribution fitted for this bin}
   \item{Beta_b}{the second shape parameter for the Beta distribution fitted for this bin}
 }}
@@ -16,7 +16,7 @@
 data(LDprofile)
 }
 \description{
-A simulated LD profile, containing example LD statisics for
+A simulated LD profile, containing example LD statistics for
 genetic distances of 0 to 0.0049, in bins of size 0.0001.
 }
 \keyword{datasets}
diff --git a/man/LR.Rd b/man/LR.Rd
index 690e369..2aec83f 100644
--- a/man/LR.Rd
+++ b/man/LR.Rd
@@ -18,7 +18,7 @@ A list containing the SNP positions and the \code{LR} values for those SNPs
 }
 \description{
 Returns the \code{|L||R|} value for each SNP location supplied to the function.
-For more information about the \code{|L||R|} diversity statistic please see Jacobs (2016).
+For more information about the \code{|L||R|} diversity statistic, please see Jacobs (2016).
 }
 \examples{
 ## load the snps example dataset
diff --git a/man/L_plus_R.Rd b/man/L_plus_R.Rd
index eb3cd74..1567e72 100644
--- a/man/L_plus_R.Rd
+++ b/man/L_plus_R.Rd
@@ -18,7 +18,7 @@ A list containing the SNP positions and the \code{L_plus_R }values for those SNP
 }
 \description{
 Returns the \eqn{{|L| \choose 2} + {|R| \choose 2}}{(|L| choose 2) + (|R| choose 2)} value for each SNP location supplied to the function.
-For more information about the \code{L_plus_R} diversity statistic please see Jacobs (2016).
+For more information about the \code{L_plus_R} diversity statistic, please see Jacobs (2016).
 }
 \examples{
 ## load the snps example dataset
diff --git a/man/Zalpha_BetaCDF.Rd b/man/Zalpha_BetaCDF.Rd
index 682b59f..b921b5a 100644
--- a/man/Zalpha_BetaCDF.Rd
+++ b/man/Zalpha_BetaCDF.Rd
@@ -10,7 +10,7 @@ Zalpha_BetaCDF(pos, x, dist, ws, LDprofile_bins, LDprofile_Beta_a,
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{dist}{A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.}
 
@@ -34,7 +34,7 @@ A list containing the SNP positions and the \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} v
 \description{
 Returns a \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} statistic, please see Jacobs (2016).
 The \eqn{Z_{\alpha}^{BetaCDF}}{Zalpha} statistic is defined as:
 \deqn{{Z_{\alpha}^{BetaCDF}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}\frac{B(r^2_{i,j};a,b)}{B(a,b)} + {|R| \choose 2}^{-1}\sum_{i,j \in R}\frac{B(r^2_{i,j};a,b)}{B(a,b)}}{2}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -43,8 +43,8 @@ the estimated a and b parameters from the LD profile.
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/Zalpha_Zscore.Rd b/man/Zalpha_Zscore.Rd
index 8c0e88e..d65fa1e 100644
--- a/man/Zalpha_Zscore.Rd
+++ b/man/Zalpha_Zscore.Rd
@@ -10,7 +10,7 @@ Zalpha_Zscore(pos, x, dist, ws, LDprofile_bins, LDprofile_rsq,
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{dist}{A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.}
 
@@ -34,7 +34,7 @@ A list containing the SNP positions and the \eqn{Z_{\alpha}^{Zscore}}{Zalpha} va
 \description{
 Returns a \eqn{Z_{\alpha}^{Zscore}}{Zalpha} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\alpha}^{Zscore}}{Zalpha} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\alpha}^{Zscore}}{Zalpha} statistic, please see Jacobs (2016).
 The \eqn{Z_{\alpha}^{Zscore}}{Zalpha} statistic is defined as:
 \deqn{{Z_{\alpha}^{Zscore}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}\frac{r^2_{i,j}-E[r^2_{i,j}]}{\sigma[r^2_{i,j}]} + {|R| \choose 2}^{-1}\sum_{i,j \in R}\frac{r^2_{i,j}-E[r^2_{i,j}]}{\sigma[r^2_{i,j}]}}{2}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -42,8 +42,8 @@ the squared correlation between a pair of SNPs, \eqn{E[r^2]}{E[r^2]} is equal to
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/Zalpha_all.Rd b/man/Zalpha_all.Rd
index 5040d38..3b2f531 100644
--- a/man/Zalpha_all.Rd
+++ b/man/Zalpha_all.Rd
@@ -11,7 +11,7 @@ Zalpha_all(pos, x = NULL, ws, dist = NULL, LDprofile_bins = NULL,
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{Optional. A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{Optional. A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{ws}{The window size which the statistics will be calculated over. This should be on the same scale as the \code{pos} vector.}
 
@@ -48,7 +48,7 @@ This includes the statistics: \code{\link{Zalpha_expected}}, \code{\link{Zalpha_
   \item For \code{\link{Zalpha_Zscore}} and \code{\link{Zbeta_Zscore}} to be calculated, the parameter \code{LDprofile_sd} must also be supplied.
   \item For \code{\link{Zalpha_BetaCDF}} and \code{\link{Zbeta_BetaCDF}} to be calculated, the parameters \code{LDprofile_Beta_a} and \code{LDprofile_Beta_b} must also be supplied.
 }
-For more information about the statistics please see Jacobs (2016).
+For more information about the statistics, please see Jacobs (2016).
 }
 \examples{
 ## load the snps and LDprofile example datasets
diff --git a/man/Zalpha_expected.Rd b/man/Zalpha_expected.Rd
index c15446d..cfcf21f 100644
--- a/man/Zalpha_expected.Rd
+++ b/man/Zalpha_expected.Rd
@@ -30,7 +30,7 @@ A list containing the SNP positions and the \eqn{Z_{\alpha}^{E[r^2]}}{Zalpha} va
 \description{
 Returns a \eqn{Z_{\alpha}^{E[r^2]}}{Zalpha} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\alpha}^{E[r^2]}}{Zalpha} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\alpha}^{E[r^2]}}{Zalpha} statistic, please see Jacobs (2016).
 The \eqn{Z_{\alpha}^{E[r^2]}} statistic is defined as:
 \deqn{{Z_{\alpha}^{E[r^2]}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}E[r^2_{i,j}] + {|R| \choose 2}^{-1}\sum_{i,j \in R}E[r^2_{i,j}]}{2}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws},
@@ -38,8 +38,8 @@ and \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/Zalpha_log_rsq_over_expected.Rd b/man/Zalpha_log_rsq_over_expected.Rd
index 07f410a..3fe024a 100644
--- a/man/Zalpha_log_rsq_over_expected.Rd
+++ b/man/Zalpha_log_rsq_over_expected.Rd
@@ -10,7 +10,7 @@ Zalpha_log_rsq_over_expected(pos, x, dist, ws, LDprofile_bins,
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{dist}{A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.}
 
@@ -32,7 +32,7 @@ A list containing the SNP positions and the \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2]
 \description{
 Returns a \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}{Zalpha} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}{Zalpha} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}{Zalpha} statistic, please see Jacobs (2016).
 The \eqn{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}{Zalpha} statistic is defined as:
 \deqn{{Z_{\alpha}^{log_{10}(r^2/E[r^2])}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}log_{10}(r^2_{i,j}/E[r^2_{i,j}]) + {|R| \choose 2}^{-1}\sum_{i,j \in R}log_{10}(r^2_{i,j}/E[r^2_{i,j}])}{2}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -40,8 +40,8 @@ the squared correlation between a pair of SNPs, and \eqn{E[r^2]}{E[r^2]} is equa
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/Zalpha_rsq_over_expected.Rd b/man/Zalpha_rsq_over_expected.Rd
index 5a77013..52846dc 100644
--- a/man/Zalpha_rsq_over_expected.Rd
+++ b/man/Zalpha_rsq_over_expected.Rd
@@ -10,7 +10,7 @@ Zalpha_rsq_over_expected(pos, x, dist, ws, LDprofile_bins, LDprofile_rsq,
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{dist}{A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.}
 
@@ -32,7 +32,7 @@ A list containing the SNP positions and the \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha
 \description{
 Returns a \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha} statistic, please see Jacobs (2016).
 The \eqn{Z_{\alpha}^{r^2/E[r^2]}}{Zalpha} statistic is defined as:
 \deqn{{Z_{\alpha}^{r^2/E[r^2]}}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}r^2_{i,j}/E[r^2_{i,j}] + {|R| \choose 2}^{-1}\sum_{i,j \in R}r^2_{i,j}/E[r^2_{i,j}]}{2}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -40,8 +40,8 @@ the squared correlation between a pair of SNPs, and \eqn{E[r^2]}{E[r^2]} is equa
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/Zbeta.Rd b/man/Zbeta.Rd
index 7fab5d6..f411b5f 100644
--- a/man/Zbeta.Rd
+++ b/man/Zbeta.Rd
@@ -9,7 +9,7 @@ Zbeta(pos, x, ws, minRandL = 4, minRL = 25, X = NULL)
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{ws}{The window size which the \eqn{Z_{\beta}}{Zbeta} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.}
 
@@ -24,7 +24,7 @@ A list containing the SNP positions and the \eqn{Z_{\beta}}{Zbeta} values for th
 }
 \description{
 Returns a \eqn{Z_{\beta}}{Zbeta} value for each SNP location supplied to the function.
-For more information about the \eqn{Z_{\beta}}{Zbeta} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\beta}}{Zbeta} statistic, please see Jacobs (2016).
 The \eqn{Z_{\beta}}{Zbeta} statistic is defined as:
 \deqn{Z_{\beta}=\frac{\sum_{i \in L,j \in R}r^2_{i,j}}{|L||R|}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, and \eqn{r^2}{r^2} is equal to the squared correlation between a pair of SNPs
diff --git a/man/Zbeta_BetaCDF.Rd b/man/Zbeta_BetaCDF.Rd
index e1b6517..8fa974b 100644
--- a/man/Zbeta_BetaCDF.Rd
+++ b/man/Zbeta_BetaCDF.Rd
@@ -10,7 +10,7 @@ Zbeta_BetaCDF(pos, x, dist, ws, LDprofile_bins, LDprofile_Beta_a,
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{dist}{A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.}
 
@@ -34,7 +34,7 @@ A list containing the SNP positions and the \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} val
 \description{
 Returns a \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} statistic, please see Jacobs (2016).
 The \eqn{Z_{\beta}^{BetaCDF}}{Zbeta} statistic is defined as:
 \deqn{Z_{\beta}^{BetaCDF}=\frac{\sum_{i \in L,j \in R}\frac{B(r^2_{i,j};a,b)}{B(a,b)}}{|L||R|}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -43,8 +43,8 @@ the estimated a and b parameters from the LD profile.
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/Zbeta_Zscore.Rd b/man/Zbeta_Zscore.Rd
index cfe5bf6..0cf6b0d 100644
--- a/man/Zbeta_Zscore.Rd
+++ b/man/Zbeta_Zscore.Rd
@@ -10,7 +10,7 @@ Zbeta_Zscore(pos, x, dist, ws, LDprofile_bins, LDprofile_rsq, LDprofile_sd,
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{dist}{A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.}
 
@@ -34,7 +34,7 @@ A list containing the SNP positions and the \eqn{Z_{\beta}^{Zscore}}{Zbeta} valu
 \description{
 Returns a \eqn{Z_{\beta}^{Zscore}}{Zbeta} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\beta}^{Zscore}}{Zbeta} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\beta}^{Zscore}}{Zbeta} statistic, please see Jacobs (2016).
 The \eqn{Z_{\beta}^{Zscore}}{Zbeta} statistic is defined as:
 \deqn{Z_{\beta}^{Zscore}=\frac{\sum_{i \in L,j \in R}\frac{r^2_{i,j}-E[r^2_{i,j}]}{\sigma[r^2_{i,j}]}}{|L||R|}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -42,8 +42,8 @@ the squared correlation between a pair of SNPs, \eqn{E[r^2]}{E[r^2]} is equal to
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/Zbeta_expected.Rd b/man/Zbeta_expected.Rd
index 5b84859..52d448c 100644
--- a/man/Zbeta_expected.Rd
+++ b/man/Zbeta_expected.Rd
@@ -30,7 +30,7 @@ A list containing the SNP positions and the \eqn{Z_{\beta}^{E[r^2]}}{Zbeta} valu
 \description{
 Returns a \eqn{Z_{\beta}^{E[r^2]}}{Zbeta} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\beta}^{E[r^2]}}{Zbeta} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\beta}^{E[r^2]}}{Zbeta} statistic, please see Jacobs (2016).
 The \eqn{Z_{\beta}^{E[r^2]}}{Zbeta} statistic is defined as:
 \deqn{Z_{\beta}^{E[r^2]}=\frac{\sum_{i \in L,j \in R}E[r^2_{i,j}]}{|L||R|}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws},
@@ -38,8 +38,8 @@ and \eqn{E[r^2]}{E[r^2]} is equal to the expected squared correlation between a
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/Zbeta_log_rsq_over_expected.Rd b/man/Zbeta_log_rsq_over_expected.Rd
index 9138232..4138545 100644
--- a/man/Zbeta_log_rsq_over_expected.Rd
+++ b/man/Zbeta_log_rsq_over_expected.Rd
@@ -10,7 +10,7 @@ Zbeta_log_rsq_over_expected(pos, x, dist, ws, LDprofile_bins,
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{dist}{A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.}
 
@@ -32,7 +32,7 @@ A list containing the SNP positions and the \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])
 \description{
 Returns a \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}}{Zbeta} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}}{Zbeta} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}}{Zbeta} statistic, please see Jacobs (2016).
 The \eqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}}{Zbeta} statistic is defined as:
 \deqn{Z_{\beta}^{log_{10}(r^2/E[r^2])}=\frac{\sum_{i \in L,j \in R}log_{10}(r^2_{i,j}/E[r^2_{i,j}])}{|L||R|}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -40,8 +40,8 @@ the squared correlation between a pair of SNPs, and \eqn{E[r^2]}{E[r^2]} is equa
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/Zbeta_rsq_over_expected.Rd b/man/Zbeta_rsq_over_expected.Rd
index 13e9251..2fdfcee 100644
--- a/man/Zbeta_rsq_over_expected.Rd
+++ b/man/Zbeta_rsq_over_expected.Rd
@@ -10,7 +10,7 @@ Zbeta_rsq_over_expected(pos, x, dist, ws, LDprofile_bins, LDprofile_rsq,
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{dist}{A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as \code{pos}.}
 
@@ -32,7 +32,7 @@ A list containing the SNP positions and the \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta}
 \description{
 Returns a \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta} value for each SNP location supplied to the function, based on
 the expected \eqn{r^2} values given an LD profile and genetic distances.
-For more information about the \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta} statistic, please see Jacobs (2016).
 The \eqn{Z_{\beta}^{r^2/E[r^2]}}{Zbeta} statistic is defined as:
 \deqn{Z_{\beta}^{r^2/E[r^2]}=\frac{\sum_{i \in L,j \in R}r^2_{i,j}/E[r^2_{i,j}]}{|L||R|}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, \eqn{r^2}{r^2} is equal to
@@ -40,8 +40,8 @@ the squared correlation between a pair of SNPs, and \eqn{E[r^2]}{E[r^2]} is equa
 }
 \details{
 The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
-real data. Care should be taken to utilise an LD profile which is representative of the population in question. The LD
-profile should consist of evenly-sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
+real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
+profile should consist of evenly sized bins of distances (for example 0.00001 cM per bin), where the value given is the (inclusive) lower
 bound of the bin.
 }
 \examples{
diff --git a/man/zalpha.Rd b/man/zalpha.Rd
index 78f503e..4b72dd0 100644
--- a/man/zalpha.Rd
+++ b/man/zalpha.Rd
@@ -9,7 +9,7 @@ Zalpha(pos, x, ws, minRandL = 4, minRL = 25, X = NULL)
 \arguments{
 \item{pos}{A numeric vector of SNP locations}
 
-\item{x}{A matrix of SNP values. Columns represent chromosomes, rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
+\item{x}{A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the \code{pos} vector. SNPs should all be biallelic.}
 
 \item{ws}{The window size which the \eqn{Z_{\alpha}}{Zalpha} statistic will be calculated over. This should be on the same scale as the \code{pos} vector.}
 
@@ -24,7 +24,7 @@ A list containing the SNP positions and the \eqn{Z_{\alpha}}{Zalpha} values for
 }
 \description{
 Returns a \eqn{Z_{\alpha}}{Zalpha} value for each SNP location supplied to the function.
-For more information about the \eqn{Z_{\alpha}}{Zalpha} statistic please see Jacobs (2016).
+For more information about the \eqn{Z_{\alpha}}{Zalpha} statistic, please see Jacobs (2016).
 The \eqn{Z_{\alpha}}{Zalpha} statistic is defined as:
 \deqn{Z_{\alpha}=\frac{{|L| \choose 2}^{-1}\sum_{i,j \in L}r^2_{i,j} + {|R| \choose 2}^{-1}\sum_{i,j \in L}r^2_{i,j}}{2}}
 where \code{|L|} and \code{|R|} are the number of SNPs to the left and right of the current locus within the given window \code{ws}, and \eqn{r^2}{r^2} is equal to the squared correlation between a pair of SNPs
-- 
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