olstest:

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

Usage

olstest(x, y, nboot = 500, SEED = TRUE, RAD = TRUE, xout = FALSE, outfun = outpro, ...)

Arguments

x
y
nboot
SEED
RAD
xout
outfun
...

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, nboot = 500, SEED = TRUE, RAD = TRUE, xout = FALSE, 
    outfun = outpro, ...) 
{
    if (SEED) 
        set.seed(2)
    m <- elimna(cbind(x, y))
    x <- as.matrix(x)
    p <- ncol(x)
    pp <- p + 1
    x <- m[, 1:p]
    y <- m[, pp]
    if (xout) {
        m <- cbind(x, y)
        flag <- outfun(x, plotit = FALSE, ...)$keep
        m <- m[flag, ]
        x <- m[, 1:p]
        y <- m[, pp]
    }
    x <- as.matrix(x)
    temp <- lsfit(x, y)
    yhat <- mean(y)
    res <- y - yhat
    test <- sum(temp$coef[2:pp]^2)
    if (RAD) 
        data <- matrix(ifelse(rbinom(length(y) * nboot, 1, 0.5) == 
            1, -1, 1), nrow = nboot)
    if (!RAD) {
        data <- matrix(runif(length(y) * nboot), nrow = nboot)
        data <- (data - 0.5) * sqrt(12)
    }
    rvalb <- apply(data, 1, olstests1, yhat, res, x)
    p.val <- sum(rvalb >= test)/nboot
    list(p.value = p.val)
  }

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