ancov2COV:
In musto101/wilcox_R: What the package does (short line)

Usage Arguments Examples

ancov2COV(x1, y1, x2, y2, tr = 0.2, test = yuen, cr = NULL, pr = TRUE, DETAILS = FALSE, cp.value = FALSE, plotit = FALSE, xlab = "X", ylab = "Y", zlab = NULL, span = 0.75, PV = TRUE, FRAC = 0.5, MC = FALSE, q = 0.5, iter = 1000, alpha = 0.05, TPM = FALSE, tau = 0.05, est = tmean, fr = 1, ...)

`x1`
`y1`
`x2`
`y2`
`tr`
`test`
`cr`
`pr`
`DETAILS`
`cp.value`
`plotit`
`xlab`
`ylab`
`zlab`
`span`
`PV`
`FRAC`
`MC`
`q`
`iter`
`alpha`
`TPM`
`tau`
`est`
`fr`
`...`

##---- 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 (x1, y1, x2, y2, tr = 0.2, test = yuen, cr = NULL, pr = TRUE, 
    DETAILS = FALSE, cp.value = FALSE, plotit = FALSE, xlab = "X", 
    ylab = "Y", zlab = NULL, span = 0.75, PV = TRUE, FRAC = 0.5, 
    MC = FALSE, q = 0.5, iter = 1000, alpha = 0.05, TPM = FALSE, 
    tau = 0.05, est = tmean, fr = 1, ...) 
{
    com.p.value = cp.value
    if (pr) 
        print("Reject if test.stat is less than or equal to crit.value")
    if (FRAC <= 0 || FRAC >= 1) 
        stop("FRAC should be a value between 0 and 1.")
    if (ncol(x1) != 2) 
        stop("Should have two covariates")
    xy1 = elimna(cbind(x1, y1))
    x1 = xy1[, 1:2]
    y1 = xy1[, 3]
    xy2 = elimna(cbind(x2, y2))
    x2 = xy2[, 1:2]
    y2 = xy2[, 3]
    n = min(c(nrow(x1), nrow(x2)))
    if (n < 50) {
        if (pr) 
            print("Warning: sample size is less than 50; critical value unknown")
    }
    if (is.null(cr)) {
        if (n >= 50 & n <= 80) 
            cr = as.vector(regYhat(c(50, 75), c(0.23, 0.264), 
                xr = n))
        if (n > 80) 
            cr = 0.27
    }
    flag0 = is.null(cr)
    flag1 = FRAC != 0.5
    flag3 = flag0 + flag1 + com.p.value + TPM
    if (flag3 > 0) {
        comp.pv = anc2COV.CV(nrow(x1), nrow(x2), iter = iter, 
            MC = MC, TPM = TPM, tau = tau)
        MV = sort(comp.pv$M)
        ic = round(alpha * iter)
        cr = MV[ic]
    }
    DONE = FALSE
    if (identical(test, qcomhd)) {
        val = ancovampG(x1, y1, x2, y2, DH = TRUE, SEED = TRUE, 
            test = qcomhd, q = q, FRAC = FRAC)
        DONE = TRUE
    }
    if (!DONE) {
        if (identical(test, yuen)) 
            val = ancovampG(x1, y1, x2, y2, DH = TRUE, SEED = TRUE, 
                test = yuen, tr = tr, FRAC = FRAC)
        if (!identical(test, yuen)) 
            val = ancovampG(x1, y1, x2, y2, DH = TRUE, SEED = TRUE, 
                test = test, FRAC = FRAC, ...)
    }
    est.dif = rung3hat(x1, y1, fr = fr, pts = val$points, est = est)$rmd - 
        rung3hat(x2, y2, pts = val$points, fr = fr, est = est)$rmd
    pavg = mean(val$results[, 3])
    if (TPM) {
        vals = val$results[, 3]
        vals = elimna(vals)
        pavg = sum(log(vals[vals <= tau]))
    }
    mpv = which(val$results[, 3] == min(val$results[, 3]))
    points = val$points
    results = val$results
    rem.res = results[mpv, 3]
    rem.points = points[mpv, ]
    points = cbind(points, est.dif)
    dimnames(points) = list(NULL, c("COV 1", "COV 2", "EST.DIF"))
    if (plotit) {
        if (is.null(zlab)) {
            if (PV) 
                zlab = "P-Value"
            if (!PV) 
                zlab = "Est.Dif"
        }
        if (PV) 
            lplot(points[, 1:2], results[, 3], xlab = xlab, ylab = ylab, 
                zlab = zlab, tick = "det", span = span)
        if (!PV) 
            lplot(points[, 1:2], est.dif, xlab = xlab, ylab = ylab, 
                zlab = zlab, tick = "det", span = span)
    }
    nk = nrow(points)
    if (!DETAILS) {
        points = NULL
        results = NULL
    }
    pval = NULL
    if (com.p.value || TPM) 
        pval = 1 - mean(pavg <= comp.pv$M)
    list(num.points.used = nk, test.stat = pavg, crit.value = cr, 
        GLOBAL.p.value = pval, min.p.val.point = rem.points, 
        min.p.value = rem.res, all.points.used = points, all.results = results[, 
            1:3])
  }