cgci:

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

Usage

cgci(x, alpha = 0.05, ks = 3.5)

Arguments

x
alpha
ks

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, alpha = 0.05, ks = 3.5) 
{
    n <- length(x)
    up <- 1 - alpha/2
    med <- median(x)
    madd <- mad(x, constant = 1)
    d <- sort(x)
    lo <- sum(x < (med - ks * madd))
    hi <- sum(x > (med + ks * madd))
    tp <- max(hi, lo)/n
    if (tp == 0) 
        tp <- 0
    if (tp > 0 && tp <= 0.01) 
        tp <- 0.01
    if (tp > 0.01 && tp <= 0.1) 
        tp <- 0.1
    if (tp > 0.1 && tp <= 0.25) 
        tp <- 0.25
    if (tp > 0.25 && tp <= 0.4) 
        tp <- 0.4
    if (tp > 0.4) 
        tp <- 0.49
    tstmn <- mean(x, trim = tp)
    ln <- floor(n * tp)
    un <- n - ln
    if (ln > 0) {
        d[1:ln] <- d[(ln + 1)]
        d[(un + 1):n] <- d[un]
    }
    den <- ((un - ln)/n)^2
    swv <- var(d)/den
    rdf <- un - ln - 1
    rval <- qt(up, rdf) * sqrt(swv/n)
    tslo <- tstmn - rval
    tshi <- tstmn + rval
    list(int = c(tslo, tshi), tp = tp)
  }

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