ks:

In musto101/wilcox_R: What the package does (short line)

Usage

ks(x, y, w = FALSE, sig = TRUE, alpha = 0.05)

Arguments

x
y
w
sig
alpha

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x, y, w = FALSE, sig = TRUE, alpha = 0.05) 
{
    x <- x[!is.na(x)]
    y <- y[!is.na(y)]
    w <- as.logical(w)
    sig <- as.logical(sig)
    tie <- logical(1)
    siglevel <- NA
    z <- sort(c(x, y))
    tie = duplicated(z)
    v <- 1
    for (i in 1:length(z)) v[i] <- abs(ecdf(x, z[i]) - ecdf(y, 
        z[i]))
    ks <- max(v)
    crit = sqrt(0 - log(alpha/2) * (length(x) + length(y))/(2 * 
        length(x) * length(y)))
    if (!w && sig && !tie) 
        siglevel <- kssig(length(x), length(y), ks)
    if (!w && sig && tie) 
        siglevel <- kstiesig(x, y, ks)
    if (w) {
        crit <- (max(length(x), length(y)) - 5) * 0.48/95 + 2.58 + 
            abs(length(x) - length(y)) * 0.44/95
        if (length(x) > 100 || length(y) > 100) 
            warning(paste("When either sample size is\ngreater than 100, the approximate critical value can be inaccurate. It is\nrecommended that the exact significance level be computed."))
        for (i in 1:length(z)) {
            temp <- (length(x) * ecdf(x, z[i]) + length(y) * 
                ecdf(y, z[i]))/length(z)
            temp <- temp * (1 - temp)
            v[i] <- v[i]/sqrt(temp)
        }
        v <- v[!is.na(v)]
        ks <- max(v) * sqrt(length(x) * length(y)/length(z))
        if (sig) 
            siglevel <- kswsig(length(x), length(y), ks)
        if (tie && sig) 
            warning(paste("Ties were detected. The reported significance level of the\nweighted Kolmogorov-Smirnov test statistic is not exact."))
    }
    list(test = ks, critval = crit, p.value = siglevel)
  }

musto101/wilcox_R documentation built on May 23, 2019, 10:52 a.m.