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

Usage Arguments Examples

1	btrim(x, tr = 0.2, grp = NA, g = NULL, dp = NULL, nboot = 599, SEED = TRUE)

`x`
`tr`
`grp`
`g`
`dp`
`nboot`
`SEED`

##---- 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, tr = 0.2, grp = NA, g = NULL, dp = NULL, nboot = 599, 
    SEED = TRUE) 
{
    if (!is.null(g)) {
        if (is.null(dp)) 
            stop("Specify a value for dp, the column containing the data")
        x = fac2list(x[, dp], x[, g])
    }
    if (is.data.frame(x)) 
        x = as.matrix(x)
    if (is.matrix(x)) 
        x <- listm(x)
    if (!is.list(x)) 
        stop("Data must be stored in a matrix or in list mode.")
    if (is.na(grp[1])) 
        grp <- c(1:length(x))
    J <- length(grp)
    nval = NA
    x = lapply(x, elimna)
    nval = lapply(x, length)
    xbar = lapply(x, mean, tr = tr)
    bvec <- array(0, c(J, 2, nboot))
    hval <- vector("numeric", J)
    if (SEED) 
        set.seed(2)
    print("Taking bootstrap samples. Please wait.")
    for (j in 1:J) {
        hval[j] <- length(x[[grp[j]]]) - 2 * floor(tr * length(x[[grp[j]]]))
        print(paste("Working on group ", grp[j]))
        xcen <- x[[grp[j]]] - mean(x[[grp[j]]], tr)
        data <- matrix(sample(xcen, size = length(x[[grp[j]]]) * 
            nboot, replace = TRUE), nrow = nboot)
        bvec[j, , ] <- apply(data, 1, trimparts, tr)
    }
    m1 <- bvec[, 1, ]
    m2 <- bvec[, 2, ]
    wvec <- 1/m2
    uval <- apply(wvec, 2, sum)
    blob <- wvec * m1
    xtil <- apply(blob, 2, sum)/uval
    blob1 <- matrix(0, J, nboot)
    for (j in 1:J) blob1[j, ] <- wvec[j, ] * (m1[j, ] - xtil)^2
    avec <- apply(blob1, 2, sum)/(length(x) - 1)
    blob2 <- (1 - wvec/uval)^2/(hval - 1)
    cvec <- apply(blob2, 2, sum)
    cvec <- 2 * (length(x) - 2) * cvec/(length(x)^2 - 1)
    testb <- avec/(cvec + 1)
    ct <- sum(is.na(testb))
    if (ct > 0) 
        print("Some bootstrap estimates of the test statistic could not be computed")
    test <- t1way(x, tr = tr, grp = grp)
    pval <- sum(test$TEST <= testb)/nboot
    e.pow = t1wayv2(x)$Explanatory.Power
    list(test = test$TEST, p.value = pval, Explanatory.Power = e.pow, 
        Effect.Size = sqrt(e.pow))
  }