update threshold vs cutoff terminology

R/RR.if.address.top.x.R

@@ -20,16 +20,16 @@
 #' @param d.pct Demographic percentage, as fraction, defining what fraction of population in each place (row) is in demographic group of interest. Required.
 #' @param popcounts Numeric vector of counts of total population in each place
 #' @param d.pct.us xxxxx
-#' @param or.tied Logical value, optional, TRUE by default, in which case ties of ranking variable with a cutoff value (value >= cutoff) are included in places within that bin.
+#' @param or.tied Logical value, optional, TRUE by default, in which case ties of ranking variable with a threshold value (value >= threshold) are included in places within that bin.
 #' @param if.multiply.e.by Optional, 0 by default. Specifies the number that environmental indicator values would be multiplied by
 #'   in the scenario where some places are addressed. Zero means those top-ranked places would have the environmental indicator set to zero,
 #'   while 0.9 would mean and 10 percent cut in the environmental indicator value.
 #' @param zones Subsets of places such as States
-#' @param mycuts optional vector of cutoff values to analyze. Default is c(50,80,90:100)
+#' @param mycuts optional vector of threshold values to analyze. Default is c(50,80,90:100)
 #' @param silent optional logical, default is TRUE, while FALSE means more information is printed
 #' @return Returns a list of results:
 #'
-#'   1. rrs data.frame, one column per environmental indicator, one row per cutoff value
+#'   1. rrs data.frame, one column per environmental indicator, one row per threshold value
 #'   2. rrs2 data.frame, Relative risks 2
 #'   3. state.tables A list
 #'   4. worst.as.pct Worst as percent, vector as long as number of environmental indicators
@@ -60,9 +60,9 @@ RR.if.address.top.x <- function(rank.by.df, e.df, d.pct, popcounts, d.pct.us, or
     for (mycut.i in 1:length(mycuts) ) {
 
       if (or.tied) {
-        worst.x <- ( rank.by.df[ , i] >= mycuts[mycut.i]) # those above given EJ %ile cutoff, or specified cutoff
+        worst.x <- ( rank.by.df[ , i] >= mycuts[mycut.i]) # those above given EJ %ile threshold, or specified threshold
       } else {
-        worst.x <- ( rank.by.df[ , i] > mycuts[mycut.i]) # those above given EJ %ile cutoff, or specified cutoff
+        worst.x <- ( rank.by.df[ , i] > mycuts[mycut.i]) # those above given EJ %ile threshold, or specified threshold
       }
       worst.x[is.na(worst.x)] <- FALSE
 
@@ -83,8 +83,8 @@ RR.if.address.top.x <- function(rank.by.df, e.df, d.pct, popcounts, d.pct.us, or
       cat('\n')
     }
 
-    # Now for a calculated cutoff, not the specified cutoff:
-    # Calculate the cutoff that will get RR==1, using specified rank.by.df and if.multiply.e.by, etc.:
+    # Now for a calculated threshold, not the specified threshold:
+    # Calculate the threshold that will get RR==1, using specified rank.by.df and if.multiply.e.by, etc.:
 
     # DOES NOT WORK YET ***
 

R/assign.map.bins.R

@@ -2,7 +2,7 @@
 #'
 #' @description Takes a vector (not matrix or df) of values and returns a vector of bin numbers.
 #' For creating color-coded maps (choropleths), assign each place (e.g., each row of a single column) to a bin.
-#' Each bin represents one map color, and is defined by cutoff values.
+#' Each bin represents one map color, and is defined by threshold values.
 #' @details
 #' The default bins 0-11 are defined as follows: \cr
 #' bin 0: PCTILE=NA \cr

R/flagged.R

@@ -1,10 +1,10 @@
-#' @title Which rows have a value above cutoff in at least one column
+#' @title Which rows have a value above threshold in at least one column
 #'
-#' @description Flags rows that have values above some cutoff in at least one column.
+#' @description Flags rows that have values above some threshold in at least one column.
 #' @details The use of na.rm=TRUE in this function means it will always ignore NA values in a given place and take the max of the valid (non-NA) values instead of returning NA when there is an NA in that row
 #' @param df Data.frame with numeric values to be checked against the threshold.
-#' @param cutoff Number that is the threshold that must be (met or) exceeded for a row to be flagged. Optional, default is 0.80
-#' @param or.tied Logical, optional, default is TRUE, in which case a value equal to the cutoff also flags the row.
+#' @param threshold Number that is the threshold that must be (met or) exceeded for a row to be flagged. Optional, default is 0.80
+#' @param or.tied Logical, optional, default is TRUE, in which case a value equal to the threshold also flags the row.
 #' @return Returns a logical vector or data.frame the shape of df
 #' @examples
 #' set.seed(999)
@@ -14,17 +14,17 @@
 #' a <- cbind(any.over.0.8=x, round(places,2))
 #' a[order(a[,1]),]
 #' @export
-flagged <- function(df, cutoff=0.80, or.tied=TRUE) {
+flagged <- function(df, threshold=0.80, or.tied=TRUE) {
 
-	# CREATE A LOGICAL VECTOR THAT IS TRUE FOR EACH ROW OF DATA FRAME WHERE AT LEAST ONE VALUE IN ROW IS >= CUTOFF (or just >CUTOFF if above.only=TRUE)
+	# CREATE A LOGICAL VECTOR THAT IS TRUE FOR EACH ROW OF DATA FRAME WHERE AT LEAST ONE VALUE IN ROW IS >= threshold (or just >threshold if above.only=TRUE)
 
   # *** Be careful to check if percentiles are 0-100 or 0-1 !!! ***
-  if (cutoff <= 1 & any(df > 1, na.rm = TRUE) ) {warning('Cutoff is <=1 so it might be a percentage as fraction, but some of data are >1 so may percentages as 0-100 not as fraction')}
+  if (threshold <= 1 & any(df > 1, na.rm = TRUE) ) {warning('threshold is <=1 so it might be a percentage as fraction, but some of data are >1 so may percentages as 0-100 not as fraction')}
 
 	if (or.tied) {
-    flag <- do.call(pmax, c(df, na.rm=TRUE)) >= cutoff
+    flag <- do.call(pmax, c(df, na.rm=TRUE)) >= threshold
 	} else {
-    flag <- do.call(pmax, c(df, na.rm=TRUE)) > cutoff
+    flag <- do.call(pmax, c(df, na.rm=TRUE)) > threshold
 	}
 	return(flag)
 }

R/flagged.by.R

@@ -1,29 +1,29 @@
 #' @title flagged.by
-#' @description Flag which cells are at or above some cutoff.
-#' @details For a matrix with a few cols of related data, find which cells are at/above (or below) some cutoff.
-#' Returns a logical matrix, with TRUE for each cell that is at/above the cutoff.
-#' Can be used in EJ analysis as 1st step in identifying places (rows) where some indicator(s) is/are at/above a cutoff, threshold value.
+#' @description Flag which cells are at or above some threshold.
+#' @details For a matrix with a few cols of related data, find which cells are at/above (or below) some threshold.
+#' Returns a logical matrix, with TRUE for each cell that is at/above the threshold.
+#' Can be used in EJ analysis as 1st step in identifying places (rows) where some indicator(s) is/are at/above a threshold, threshold value.
 #'
-#' @param x Data.frame or matrix of numbers to be compared to cutoff value.
-#' @param cutoff Numeric. The threshold or cutoff to which numbers are compared. Default is arithmetic mean of row. Usually one number, but can be a vector of same length as number of rows, in which case each row can use a different cutoff.
-#' @param or.tied Logical. Default is FALSE, which means we check if number in x is greater than the cutoff (>). If TRUE, check if greater than or equal (>=).
-#' @param below Logical. Default is FALSE. If TRUE, uses > or >= cutoff. If FALSE, uses < or <= cutoff.
+#' @param x Data.frame or matrix of numbers to be compared to threshold value.
+#' @param threshold Numeric. The threshold or threshold to which numbers are compared. Default is arithmetic mean of row. Usually one number, but can be a vector of same length as number of rows, in which case each row can use a different threshold.
+#' @param or.tied Logical. Default is FALSE, which means we check if number in x is greater than the threshold (>). If TRUE, check if greater than or equal (>=).
+#' @param below Logical. Default is FALSE. If TRUE, uses > or >= threshold. If FALSE, uses < or <= threshold.
 #' @param ... optional additional parameters to pass to [analyze.stuff::cols.above.which()]
 #' @return Returns a logical matrix the same size as x.
 #' @seealso cols.above.which,  another name for the exact same function.
-#' @seealso cols.above.count or cols.above.pct to see, for each row, count or fraction of columns with numbers at/above/below cutoff.
-#' @seealso flagged.only.by to find cells that are the only one in the row that is at/above/below the cutoff.
+#' @seealso cols.above.count or cols.above.pct to see, for each row, count or fraction of columns with numbers at/above/below threshold.
+#' @seealso flagged.only.by to find cells that are the only one in the row that is at/above/below the threshold.
 #' @seealso rows.above.count, rows.above.pct, rows.above.which
 #' @examples
-#' out <- flagged.by(x<-data.frame(a=1:10, b=rep(7,10), c=7:16), cutoff=7)
+#' out <- flagged.by(x<-data.frame(a=1:10, b=rep(7,10), c=7:16), threshold=7)
 #' x; out # default is or.tied=FALSE
-#' out <- flagged.by(data.frame(a=1:10, b=rep(7,10), c=7:16), cutoff=7, or.tied=TRUE, below=TRUE)
+#' out <- flagged.by(data.frame(a=1:10, b=rep(7,10), c=7:16), threshold=7, or.tied=TRUE, below=TRUE)
 #' out
 #' out <- flagged.by(data.frame(a=1:10, b=rep(7,10), c=7:16) )
 #' # Compares each number in each row to the row's mean.
 #' out
-#' @note Future work: these functions could have wts, na.rm, & allow cutoffs or benchmarks as a vector (not just 1 number), & have benchnames.
+#' @note Future work: these functions could have wts, na.rm, & allow cutpoints or benchmarks as a vector (not just 1 number), & have benchnames.
 #' @export
-flagged.by <- function(x, cutoff, or.tied, below, ...) {
-  cols.above.which(x=x, cutoff=cutoff, or.tied=or.tied, ...)
+flagged.by <- function(x, threshold, or.tied, below, ...) {
+  analyze.stuff::cols.above.which(x=x, cutoff=threshold, or.tied=or.tied, ...)
 }

R/flagged.only.by.R

@@ -1,34 +1,34 @@
 #' @title flagged.only.by
-#' @description Flag which cells are the only one in the row that is at/above a cutoff (find rows that meet only 1 of several criteria).
-#' @details For a data.frame with a few cols of related data, find which cells are the only one in the row that is at/above some cutoff.
+#' @description Flag which cells are the only one in the row that is at/above a threshold (find rows that meet only 1 of several criteria).
+#' @details For a data.frame with a few cols of related data, find which cells are the only one in the row that is at/above some threshold.
 #'   This can find rows that meet only 1 of several criteria, for example.
 #'   Returns a logical matrix or data.frame, with TRUE for each cell that meets the test.
-#'   Can be used in EJ analysis in identifying places (rows) that were only flagged because one of the indicator(s) is at/above a cutoff, threshold value.
+#'   Can be used in EJ analysis in identifying places (rows) that were only flagged because one of the indicator(s) is at/above a threshold, threshold value.
 #'   For example, if there were four criteria to be met in flagging a location, this function identifies
 #'   places that met only one of the criteria, and can show which one was met.
 #'
-#' @param x Data.frame or matrix of numbers to be compared to cutoff value.
-#' @param cutoff The numeric threshold or cutoff to which numbers are compared. Default is 8! Usually one number, but can be a vector of same length as number of rows, in which case each row can use a different cutoff.
-#' @param or.tied Logical. Default is FALSE, which means we check if number in x is greater than the cutoff (>). If TRUE, check if greater than or equal (>=).
-#' @param below Logical. Default is FALSE. If TRUE, uses > or >= cutoff. If FALSE, uses < or <= cutoff.
+#' @param x Data.frame or matrix of numbers to be compared to threshold value.
+#' @param threshold The numeric threshold or threshold to which numbers are compared. Default is 8! Usually one number, but can be a vector of same length as number of rows, in which case each row can use a different threshold.
+#' @param or.tied Logical. Default is FALSE, which means we check if number in x is greater than the threshold (>). If TRUE, check if greater than or equal (>=).
+#' @param below Logical. Default is FALSE. If TRUE, uses > or >= threshold. If FALSE, uses < or <= threshold.
 #' @return Returns a logical matrix the same size as x.
-#' @seealso flagged.by or cols.above.which to see which cells are at/above/below some cutoff
-#' @seealso cols.above.count to see, for each row, how many columns are at/above some cutoff
-#' @seealso cols.above.percent to see, for each row, what fraction of columns are at/above some cutoff
+#' @seealso flagged.by or cols.above.which to see which cells are at/above/below some threshold
+#' @seealso cols.above.count to see, for each row, how many columns are at/above some threshold
+#' @seealso cols.above.percent to see, for each row, what fraction of columns are at/above some threshold
 #' @keywords EJ
 #' @examples
-#'   out <- flagged.only.by(x<-data.frame(a=1:10, b=rep(7,10), c=7:16), cutoff=7)
+#'   out <- flagged.only.by(x<-data.frame(a=1:10, b=rep(7,10), c=7:16), threshold=7)
 #'   x;  out # default is or.tied=FALSE
-#'   out <- flagged.only.by(data.frame(a=1:10, b=rep(7,10), c=7:16), cutoff=7,
+#'   out <- flagged.only.by(data.frame(a=1:10, b=rep(7,10), c=7:16), threshold=7,
 #'   or.tied=TRUE, below=TRUE)
 #'   out
 #'   out <- flagged.only.by(data.frame(a=1:10, b=rep(7,10), c=7:16) )
-#'   # Compares each number in each row to the default cutoff.
+#'   # Compares each number in each row to the default threshold.
 #'   out
-#' @note Future work: these functions could have wts, na.rm, & allow cutoffs or benchmarks as a vector (not just 1 number), & have benchnames.
+#' @note Future work: these functions could have wts, na.rm, & allow cutpoints or benchmarks as a vector (not just 1 number), & have benchnames.
 #' @export
-flagged.only.by <- function(x, cutoff=8, or.tied=FALSE, below=FALSE) {
-  above <- flagged.by(df.bins=df.bins, cutoff=cutoff, or.tied=or.tied)
+flagged.only.by <- function(x, threshold=8, or.tied=FALSE, below=FALSE) {
+  above <- flagged.by(df.bins=df.bins, threshold=threshold, or.tied=or.tied)
   onlyby <- above
   onlyby[rowSums(onlyby) > 1, ] <- 0
   return(onlyby)

R/make.bin.pctile.cols.R

@@ -3,7 +3,7 @@
 #' @description This function just combines [make.pctile.cols()] and [make.bin.cols()].
 #' Takes a data.frame of values and returns a data.frame (or matrix) of percentiles,
 #' showing the percentile of a value within all values in its column, as well as bin numbers,
-#' showing what bin each falls into, based on specified cutoffs defining bins. \cr\cr
+#' showing what bin each falls into, based on specified cutpoints defining bins. \cr\cr
 #' ** Work in progress/ not fully tested, e.g., need to test if all code below works with both as.df=TRUE and as.df=FALSE
 #' @param raw.data.frame Data.frame of values
 #' @param weights Optional Numeric vector of weights to create weighted percentiles, such as population-weighted quantiles. Unweighted if not specified. Vector same length as number of rows in data.frame.

ejanalysis.html

@@ -1155,7 +1155,7 @@ <h3>Value</h3>
 
 <h3>Note</h3>
 
-<p>Future work: these functions could have wts, na.rm, &amp; allow cutoffs or benchmarks as a vector (not just 1 number), &amp; have benchnames.
+<p>Future work: these functions could have wts, na.rm, &amp; allow cutpoints or benchmarks as a vector (not just 1 number), &amp; have benchnames.
 </p>
 
 
@@ -1245,7 +1245,7 @@ <h3>Value</h3>
 
 <h3>Note</h3>
 
-<p>Future work: these functions could have wts, na.rm, &amp; allow cutoffs or benchmarks as a vector (not just 1 number), &amp; have benchnames.
+<p>Future work: these functions could have wts, na.rm, &amp; allow cutpoints or benchmarks as a vector (not just 1 number), &amp; have benchnames.
 </p>
 
 
@@ -2414,7 +2414,7 @@ <h3>Description</h3>
 <p>This function just combines <code><a href="#make.pctile.cols">make.pctile.cols()</a></code> and <code><a href="#make.bin.cols">make.bin.cols()</a></code>.
 Takes a data.frame of values and returns a data.frame (or matrix) of percentiles,
 showing the percentile of a value within all values in its column, as well as bin numbers,
-showing what bin each falls into, based on specified cutoffs defining bins. <br><br>
+showing what bin each falls into, based on specified cutpoints defining bins. <br><br>
 ** Work in progress/ not fully tested, e.g., need to test if all code below works with both as.df=TRUE and as.df=FALSE
 </p>