man2pb:

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

Usage

man2pb(x, y, alpha = 0.05, nboot = NA, crit = NA)

Arguments

x
y
alpha
nboot
crit

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, alpha = 0.05, nboot = NA, crit = NA) 
{
    if (!is.list(x) && !is.matrix(x)) 
        stop("Data must be stored in a matrix or in list mode.")
    if (!is.list(y) && !is.matrix(y)) 
        stop("Data must be stored in a matrix or in list mode.")
    if (is.list(x)) {
        matx <- matrix(0, length(x[[1]]), length(x))
        for (j in 1:length(x)) matx[, j] <- x[[j]]
    }
    if (is.list(y)) {
        maty <- matrix(0, length(y[[1]]), length(y))
        for (j in 1:length(y)) maty[, j] <- y[[j]]
    }
    if (is.matrix(x)) {
        matx <- x
    }
    if (is.matrix(y)) {
        maty <- y
    }
    if (ncol(matx) != ncol(maty)) 
        stop("The number of variables for group 1 is not equal to the number for group 2")
    if (sum(is.na(matx) >= 1)) 
        matx <- elimna(matx)
    if (sum(is.na(maty) >= 1)) 
        maty <- elimna(maty)
    J <- ncol(matx)
    connum <- ncol(matx)
    if (is.na(nboot)) {
        if (ncol(matx) <= 4) 
            nboot <- 2000
        if (ncol(matx) > 4) 
            nboot <- 5000
    }
    if (ncol(matx) == 2) {
        if (alpha == 0.05) 
            crit <- 0.0125
        if (alpha == 0.025) 
            crit <- 0.006
        if (alpha == 0.01) 
            crit <- 0.0015
    }
    if (ncol(matx) == 3) {
        if (alpha == 0.05) 
            crit <- 0.007
        if (alpha == 0.025) 
            crit <- 0.003
        if (alpha == 0.01) 
            crit <- 0.001
    }
    if (ncol(matx) == 4) {
        if (alpha == 0.05) 
            crit <- 0.0055
        if (alpha == 0.025) 
            crit <- 0.002
        if (alpha == 0.01) 
            crit <- 5e-04
    }
    if (ncol(matx) == 5) {
        if (alpha == 0.05) 
            crit <- 0.0044
        if (alpha == 0.025) 
            crit <- 0.0016
        if (alpha == 0.01) 
            crit <- 5e-04
    }
    if (ncol(matx) == 6) {
        if (alpha == 0.05) 
            crit <- 0.0038
        if (alpha == 0.025) 
            crit <- 0.0018
        if (alpha == 0.01) 
            crit <- 4e-04
    }
    if (ncol(matx) == 7) {
        if (alpha == 0.05) 
            crit <- 0.0028
        if (alpha == 0.025) 
            crit <- 0.001
        if (alpha == 0.01) 
            crit <- 2e-04
    }
    if (ncol(matx) == 8) {
        if (alpha == 0.05) 
            crit <- 0.0026
        if (alpha == 0.025) 
            crit <- 0.001
        if (alpha == 0.01) 
            crit <- 2e-04
    }
    if (ncol(matx) > 8) {
        if (alpha == 0.025) 
            warning("Can't determine a critical value when alpha=.025 and the number of groups exceeds 8.")
        nmin <- min(nrow(matx), nrow(maty))
        if (alpha == 0.05) {
            if (nmin < 100) 
                wval <- smmcrit(60, ncol(matx))
            if (nmin >= 100) 
                wval <- smmcrit(300, ncol(matx))
            wval <- 0 - wval
            crit <- pnorm(wval)
        }
        if (alpha == 0.01) {
            if (nmin < 100) 
                wval <- smmcrit01(60, ncol(matx))
            if (nmin >= 100) 
                wval <- smmcrit01(300, ncol(matx))
            wval <- 0 - wval
            crit <- pnorm(wval)
        }
    }
    if (is.na(crit)) 
        warning("Critical values can be determined for alpha=.05, .025 and .01 only")
    icl <- ceiling(crit * nboot)
    icu <- ceiling((1 - crit) * nboot)
    set.seed(2)
    print("Taking bootstrap samples. Please wait.")
    bootx <- bootdep(matx, tr = 0.2, nboot)
    booty <- bootdep(maty, tr = 0.2, nboot)
    test <- 1
    for (j in 1:connum) {
        test[j] <- sum(bootx[, j] < booty[, j])/nboot
        if (test[j] > 0.5) 
            test[j] <- 1 - test[j]
    }
    output <- matrix(0, connum, 5)
    dimnames(output) <- list(NULL, c("variable #", "psihat", 
        "test", "ci.lower", "ci.upper"))
    tmeanx <- apply(matx, 2, mean, trim = 0.2)
    tmeany <- apply(maty, 2, mean, trim = 0.2)
    psi <- 1
    for (ic in 1:connum) {
        output[ic, 2] <- tmeanx[ic] - tmeany[ic]
        output[ic, 1] <- ic
        output[ic, 3] <- test[ic]
        temp <- sort(bootx[, ic] - booty[, ic])
        print(length(temp))
        output[ic, 4] <- temp[icl]
        output[ic, 5] <- temp[icu]
    }
    list(output = output, crit.value = crit)
  }

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