BCI:

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

Usage

BCI(Z, Zr, ab = NULL, abH, B, level)

Arguments

Z
Zr
ab
abH
B
level

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 (Z, Zr, ab = NULL, abH, B, level) 
{
    p = ncol(Z)
    n = nrow(Z)
    abhatH.v = matrix(NA, B)
    Index.m = matrix(NA, n, B)
    t1 = 0
    t2 = 0
    for (i in 1:B) {
        U = runif(n, min = 1, max = n + 1)
        index = floor(U)
        Index.m[, i] = index
        Zrb = Zr[index, ]
        SH = MeanCov(Zrb)$S
        thetaH = MLEst(SH)
        abhatH = thetaH[1] * thetaH[2]
        abhatH.v[i] = abhatH
        if (abhatH < abH) {
            t2 = t2 + 1
        }
    }
    abhatH.v = abhatH.v[!is.na(abhatH.v)]
    SEBH = sd(abhatH.v)
    CI2 = BpBCa(Zr, abhatH.v, t2, level)
    Results = list(CI = CI2[[1]], pv = CI2[[2]])
    return(Results)
  }

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