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##' Central Tendency estimates for variables
##'
##' This is needed for the creation of summaries and predicted values
##' of regression models. It takes a data frame and returns a new data
##' frame with one row in which the mean or mode of the columns is
##' reported.
##'
##' @param x a data frame
##' @return a data frame with the same variables and one row, the summary indicators.
##' @author Paul E. Johnson \email{pauljohn@@ku.edu}
##' @export
##' @examples
##' myDat <- data.frame(x=rnorm(100), y=rpois(100,l=4), z = cut(rnorm(100), c(-10,-1,0,10)))
##' centralValues(myDat)
centralValues <- function(x){
if( !is.data.frame(x)) stop("represent: x must be a data frame!")
nc <- NCOL(x)
nams <- colnames(x)
represents <- x[1, , drop = FALSE] ## row 1, so we inherit the df's properties, labels
for (i in 1: nc) {
xvar <- x[ , i]
if (is.numeric(xvar)){
represents[1, i] <- mean(xvar, na.rm = TRUE)
} else if (is.factor(xvar)) {
xvartable <- table(xvar)
xvarmode <- names(xvartable)[which.max(xvartable)]
represents[1, i] <- xvarmode
} else {
xvar <- factor(xvar)
xvartable <- table(xvar)
xvarmode <- names(xvartable)[which.max(xvartable)]
represents[1, i] <- xvarmode
}
}
as.data.frame(represents)
rownames(represents) <- NULL
represents
}
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