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#' Generalized logit and inverse logit function
#'
#' Compute generalized logit and generalized inverse logit functions.
#'
#'
#' The generalized logit function takes values on [min, max] and transforms
#' them to span [-Inf,Inf] it is defined as:
#'
#' \deqn{y = log(\frac{p}{(1-p)})}{y = log(p/(1-p))}
#'
#' where
#'
#' \deqn{p=\frac{(x-min)}{(max-min)}}{p=(x-min)/(max-min)}
#'
#' The generalized inverse logit function provides the inverse transformation:
#'
#' \deqn{x = p' (max-min) + min}{x = p * (max-min) + min}
#'
#' where
#'
#' \deqn{p'=\frac{exp(y)}{(1+exp(y))}}{exp(y)/(1+exp(y))}
#'
#' @aliases logit inv.logit
#' @param x value(s) to be transformed
#' @param min Lower end of logit interval
#' @param max Upper end of logit interval
#' @return Transformed value(s).
#' @author Gregory R. Warnes \email{greg@@warnes.net}
#' @seealso \code{\link[car]{logit}}
#' @keywords math
#' @examples
#'
#'
#' x <- seq(0, 10, by = 0.25)
#' xt <- logit(x, min = 0, max = 10)
#' cbind(x, xt)
#'
#' y <- inv.logit(xt, min = 0, max = 10)
#' cbind(x, xt, y)
#' @export
logit <- function(x, min = 0, max = 1) {
p <- (x - min) / (max - min)
log(p / (1 - p))
}
#' @rdname logit
#' @export
inv.logit <- function(x, min = 0, max = 1) {
p <- exp(x) / (1 + exp(x))
p <- ifelse(is.na(p) & !is.na(x), 1, p) # fix problems with +Inf
p * (max - min) + min
}
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