mee:

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

Usage

mee(x, y, alpha = 0.05)

Arguments

x
y
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, alpha = 0.05) 
{
    x <- x[!is.na(x)]
    y <- y[!is.na(y)]
    xy <- c(x, y)
    tiexy <- sum(abs(c(1:length(xy)) - sort(rank(xy))))
    if (tiexy > 0) {
        print("Warning: Tied values detected")
        print("so even if distributions are identical,")
        print("P(X<Y) is not necessarily equal to .5")
    }
    u <- outer(x, y, FUN = "<")
    p1 <- 0
    p2 <- 0
    for (j in 1:length(y)) {
        temp <- outer(u[, j], u[, j])
        p1 <- p1 + sum(temp) - sum(u[, j] * u[, j])
    }
    for (i in 1:length(x)) {
        temp <- outer(u[i, ], u[i, ])
        p2 <- p2 + sum(temp) - sum(u[i, ] * u[i, ])
    }
    p <- sum(u)/(length(x) * length(y))
    p1 <- p1/(length(x) * length(y) * (length(x) - 1))
    p2 <- p2/(length(x) * length(y) * (length(y) - 1))
    b1 <- (p1 - p^2)/(p - p^2)
    b2 <- (p2 - p^2)/(p - p^2)
    A <- ((length(x) - 1) * b1 + 1)/(1 - 1/length(y)) + ((length(y) - 
        1) * b2 + 1)/(1 - 1/length(x))
    nhat <- length(x) * length(y)/A
    crit <- (qnorm(1 - alpha/2))^2/nhat
    D <- sqrt(crit * (p * (1 - p) + 0.25 * crit))
    low <- (p + 0.5 * crit - D)/(1 + crit)
    hi <- (p + 0.5 * crit + D)/(1 + crit)
    list(phat = p, ci = c(low, hi))
  }

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