Nothing
###################################################################
# Print for compind
# Arg:
# object belonging to compind class
#
# Returns:
# Tells the type of controls used and produces the ranks predicted finally.
print.compind <- function(x, ...)
{
cat("\nCall:\n", deparse(x$call), "\n", sep = "")
cat("\nIndex is calculated using", x$ctr$aggregation[1], "aggregation,", x$ctr$normalization[1], "normalization technique,",
x$ctr$weights[1], "weights used. \nMissing values treated using", x$ctr$missingindicator[1], "method and cleaning method used was", x$ctr$cleaning[1], " \n")
if (!is.null(x$ctr$setmax) & !is.null(x$ctr$setmin)){
NonNAindex.max <- which(!is.na(x$ctr$setmax))
maxcol <- colnames(x$indicator.array[,NonNAindex.max,1, drop=FALSE])
max.vals <- x$ctr$setmax[NonNAindex.max]
NonNAindex.min <- which(!is.na(x$ctr$setmin))
mincol <- colnames(x$indicator.array[,NonNAindex.min, 1, drop=FALSE])
min.vals <- x$ctr$setmin[NonNAindex.min]
cat("Indicator", maxcol , "are capped at maximum value of", max.vals, ".\n")
cat("Indicator", mincol , "are set at minimum value of", min.vals, ".\n")
}
if (!is.null(x$ctr$setmax) & is.null(x$ctr$setmin)){
NonNAindex.max <- which(!is.na(x$ctr$setmax))
maxcol <- colnames(x$indicator.array[,NonNAindex.max, 1])
max.vals <- x$ctr$setmax[NonNAindex.max]
cat("Indicator", maxcol , "are capped at maximum value of", max.vals, ".\n")
}
if (is.null(x$ctr$setmax) & !is.null(x$ctr$setmin)){
NonNAindex.min <- which(!is.na(x$ctr$setmin))
mincol <- colnames(x$indicator.array[, NonNAindex.min, 1])
min.vals <- x$ctr$setmin[NonNAindex.min]
cat("Indicator", mincol , "are set at minimum value of", min.vals, ".\n")
}
cat("\nRanked countries:\n")
ret <- x$ranking[order(x$ranking[,1]),, drop=FALSE]
print(ret)
}
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