#' simFuzz
#'
#' simFuzz is a function to generate simulated continous data for cluster analysis
#'
#' @param numVars creates n vars that are all in fuzzy subset relationships. Must be greater than 2. Default is 2.
#' @param numCases is the number of cases to include in the generated fake data set. Must be greater than 1. Default is 50.
#' @return A data frame with one column per variable.
#' @export
#
simFuzz <- function(numVars = 2, numCases = 50) {
# create a data frame of random numbers
preScatter <- data.frame(replicate(numVars,sample(0:1000,numCases,rep=TRUE)))
# convert to decimals
preScatter <- preScatter/1000
# name the columns
colnames(preScatter) <- LETTERS[1:numVars]
# generate a blank data frame to hold the actual generated data
genScatter <- data.frame(matrix(NA, nrow = numCases, ncol = numVars))
# name the columns
colnames(genScatter) <- LETTERS[1:numVars]
# move the first column to the generated data frame
genScatter$A <- preScatter$A
# for the other columns, place above the diagonal with the transform below
for (i in 2:ncol(preScatter)) {
for(j in 1:nrow(preScatter)) {
genScatter[j,i] <- (1- preScatter[j,1]) * preScatter[j,i] + preScatter[j,1]
}
}
# send back the generated data frame
return(genScatter)
}
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