linconMpb:

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

Usage

linconMpb(x, alpha = 0.05, nboot = 1000, grp = NA, est = tmean, con = 0, bhop = FALSE, SEED = TRUE, PDIS = FALSE, J = NULL, p = NULL, ...)

Arguments

x
alpha
nboot
grp
est
con
bhop
SEED
PDIS
J
p
...

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, nboot = 1000, grp = NA, est = tmean, 
    con = 0, bhop = FALSE, SEED = TRUE, PDIS = FALSE, J = NULL, 
    p = NULL, ...) 
{
    con <- as.matrix(con)
    if (is.matrix(x) || is.data.frame(x)) {
        if (is.null(J) && is.null(p)) 
            stop("Specify J or P")
        x = MAT2list(x, p = p, J = J)
    }
    if (!is.list(x)) 
        stop("Data must be stored in list mode.")
    if (!is.na(sum(grp))) {
        xx <- list()
        for (i in 1:length(grp)) xx[[i]] <- x[[grp[i]]]
        x <- xx
    }
    J <- length(x)
    nullvec = rep(0, ncol(x[[1]]))
    bplus = nboot + 1
    tempn <- 0
    mvec <- list
    for (j in 1:J) {
        x[[j]] <- elimna(x[[j]])
    }
    Jm <- J - 1
    if (sum(con^2) == 0) {
        ncon <- (J^2 - J)/2
        con <- matrix(0, J, ncon)
        id <- 0
        for (j in 1:Jm) {
            jp <- j + 1
            for (k in jp:J) {
                id <- id + 1
                con[j, id] <- 1
                con[k, id] <- 0 - 1
            }
        }
    }
    ncon <- ncol(con)
    if (nrow(con) != J) 
        stop("Something is wrong with con; the number of rows does not match the number of groups.")
    if (!bhop) {
        if (alpha == 0.05) {
            dvec <- c(0.05, 0.025, 0.0169, 0.0127, 0.0102, 0.00851, 
                0.0073, 0.00639, 0.00568, 0.00511)
            if (ncon > 10) {
                avec <- 0.05/c(11:ncon)
                dvec <- c(dvec, avec)
            }
        }
        if (alpha == 0.01) {
            dvec <- c(0.01, 0.005, 0.00334, 0.00251, 0.00201, 
                0.00167, 0.00143, 0.00126, 0.00112, 0.00101)
            if (ncon > 10) {
                avec <- 0.01/c(11:ncon)
                dvec <- c(dvec, avec)
            }
        }
        if (alpha != 0.05 && alpha != 0.01) {
            dvec <- alpha/c(1:ncon)
        }
    }
    if (bhop) 
        dvec <- (ncon - c(1:ncon) + 1) * alpha/ncon
    bvec <- array(NA, c(J, nboot, ncol(x[[1]])))
    if (SEED) 
        set.seed(2)
    nvec = lapply(x, nrow)
    for (j in 1:J) {
        data <- matrix(sample(nvec[[j]], size = nvec[[j]] * nboot, 
            replace = TRUE), nrow = nboot)
        bvec[j, , ] <- apply(data, 1, linconMpb.sub, x[[j]], 
            est, ...)
    }
    test <- NA
    for (d in 1:ncon) {
        tv = matrix(0, nboot, ncol(x[[1]]))
        estit = rep(0, ncol(x[[1]]))
        for (j in 1:J) {
            tv = tv + con[j, d] * bvec[j, , ]
            estit = estit + con[j, d] * apply(x[[j]], 2, est, 
                ...)
        }
        if (!PDIS) 
            m1 = cov(tv)
        tv = rbind(tv, nullvec)
        if (!PDIS) 
            dv = mahalanobis(tv, center = estit, m1)
        if (PDIS) 
            dv = pdis(tv, center = estit)
        test[d] = 1 - sum(dv[bplus] >= dv[1:nboot])/nboot
    }
    output <- matrix(0, ncon, 3)
    dimnames(output) <- list(NULL, c("con.num", "p.value", "p.crit"))
    temp2 <- order(0 - test)
    zvec <- dvec[1:ncon]
    sigvec <- (test[temp2] >= zvec)
    output[temp2, 3] <- zvec
    for (ic in 1:ncol(con)) {
        output[ic, 1] <- ic
        output[ic, 2] <- test[ic]
    }
    num.sig <- sum(output[, 2] <= output[, 3])
    list(output = output, con = con, num.sig = num.sig)
  }

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