Nothing
#' @title Atkinson Index of Inequality
#'
#' @description Calculates the Atkinson index A. This inequality measure is especially good at determining which end of the distribution is contributing most to the observed inequality.
#'
#' @param x a vector of data values of non-negative elements.
#' @param n a vector of frequencies of the same length as \code{x}.
#' @param epsilon a parameter of the inequality measure (if \code{NULL}, the default parameter (0.5) of the respective measure is used).
#' @param na.rm logical. Should missing values be removed? Defaults is set to \code{FALSE}.
#' @param \dots additional arguements (currently ignored)
#' @details
#' epsilon = 0,5: little inequality aversion
#' epsilon = 1,0: medium inequality aversion
#' epsilon = 2,0: great inequality aversion
#'
#' @references
#' Cowell, F. A. (2000) Measurement of Inequality in Atkinson, A. B. / Bourguignon, F. (Eds): \emph{Handbook of Income Distribution}. Amsterdam.
#'
#' Cowell, F. A. (1995) \emph{Measuring Inequality} Harvester Wheatshef: Prentice Hall.
#'
#' @seealso \code{\link{Herfindahl}}, \code{\link{Rosenbluth}}, \code{\link{Gini}}. For more details see the \dQuote{Indices} vignette.
#'
#' @examples
#' if (interactive()) {
#' # generate a vector (of incomes)
#' # y <- c(80, 60, 10, 20, 30)
#' # Entropy 1.392321
#' # Maximum Entropy 1.609438
#' # Normalized Entropy 0.865098
#' # Exponential Index 0.248498
#' # Herfindahl 0.285000
#' # Normalized Herfindahl 0.106250
#' # Gini Coefficient 0.360000
#' # Concentration Coefficient 0.450000
#'
#' x <- c(778, 815, 857, 888, 925, 930, 965, 990, 1012)
#'
#' # compute Atkinson coefficient with epsilon=0.5
#' Atkinson(x, epsilon=0.5)
#'
#' w <- c(10, 15, 20, 25, 40, 20, 30, 35, 45, 90)
#'}
#'
#' @export
#' @rdname Atkinson
`Atkinson` <-function(x, n = rep(1, length(x)), epsilon=NULL, na.rm=FALSE, ...) UseMethod("Atkinson")
NULL
#' @export
#' @rdname Atkinson
`Atkinson.default` <- function(x, n = rep(1, length(x)), epsilon = NULL, na.rm = FALSE, ...){
x <- rep(x, n) # same handling as Lc and Gini
if(na.rm) x <- na.omit(x)
if (any(is.na(x)) || any(x < 0)) return(NA_real_)
if(is.null(epsilon)) epsilon <- 0.5
if(epsilon==1)
idx <- 1 - (exp(mean(log(x)))/mean(x))
else
{
x <- (x/mean(x))^(1-epsilon)
idx <- 1 - mean(x)^(1/(1-epsilon))
}
print(idx, digits = max(3, getOption("digits") - 3))
}### end -- Atkinson function
NULL
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.