#' Helper function that calculates the mode of a vector with no missing values
#'
#' \code{impute_mode} returns a vector of values imputed from the mode(s) of \code{x}.
#'
#' @param x A vector.
#' @param n The number of values to impute. Only relevant when when there is not a unique mode.
#' @param tiebreaker How to break "ties" if there is not a single unique mode. The default is
#' "random", which samples randomly with replacement from the different modes.
#' @return The output of \code{impute_mode} is a vector of imputed values of length \code{n}
#' @export
#' @family imputers
#' @examples
#' x <- c("mode", "mode", "other", NA, NA)
#'
#' # Impute mode
#' x_impute <- impute(x, impute_mode)
#'
#' # Compare
#' data.frame(x, x_impute)
impute_mode <- function(x, n=1, tiebreaker="random") {
# Check x
if (missing(x)) {
stop("Please provide a vector x to compute the mode", call.=FALSE)
} else if (any(is.na(x))) {
stop("x cannot contain any NAs")
}
# Check n
if (!is.numeric(n) || n < 1) {
stop("n must be a positive integer", call.=FALSE)
}
n <- floor(n)
# Check tiebreaker
tiebreaker <- match.arg(tiebreaker)
# Tabulate
x_tab <- table_rcpp(x)
# Sort in decreasing order
x_tab <- sort(x_tab, decreasing=TRUE)
# Mode(s)
x_mode <- names(x_tab[x_tab == max(x_tab)])
# Handle ties
if (length(x_mode) > 1) {
if (tiebreaker == "random") {
x_mode <- sample(x_mode, size=n, replace=TRUE)
}
}
# Convert back to numeric, if applicable
if (is.numeric(x)) {
x_mode <- as.numeric(x_mode)
}
# Return
x_mode
}
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