hc4wtest:

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

Usage

hc4wtest(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)
    x <- as.matrix(x)
    temp <- cbind(x, y)
    temp <- elimna(temp)
    pval <- ncol(temp) - 1
    x <- temp[, 1:pval]
    y <- temp[, pval + 1]
    if (xout) {
        flag <- outfun(x, ...)$keep
        x <- as.matrix(x)
        x <- x[flag, ]
        y <- y[flag]
        x <- as.matrix(x)
    }
    x <- as.matrix(x)
    p <- ncol(x)
    pp <- p + 1
    temp <- lsfit(x, y)
    Rsq = ols(x, y)$R.squared
    yhat <- mean(y)
    res <- y - yhat
    s <- olshc4(x, y)$cov[-1, -1]
    si <- solve(s)
    b <- temp$coef[2:pp]
    wtest <- t(b) %*% si %*% b
    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, lstest4, yhat, res, x)
    sum <- sum(rvalb >= wtest[1, 1])
    p.val <- sum/nboot
    list(p.value = p.val, R.squared = Rsq)
  }

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