linconm:

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

Usage

linconm(x, con = 0, est = onestep, alpha = 0.05, nboot = 500, pr = TRUE, ...)

Arguments

x
con
est
alpha
nboot
pr
...

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, con = 0, est = onestep, alpha = 0.05, nboot = 500, 
    pr = TRUE, ...) 
{
    if (pr) {
        print("Note: confidence intervals are adjusted to control FWE")
        print("But p-values are not adjusted to control FWE")
    }
    if (is.matrix(x)) 
        x <- listm(x)
    con <- as.matrix(con)
    if (!is.list(x)) 
        stop("Data must be stored in list mode.")
    J <- length(x)
    Jm <- J - 1
    d <- (J^2 - J)/2
    if (sum(con^2) == 0) {
        con <- matrix(0, J, d)
        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
            }
        }
    }
    if (nrow(con) != length(x)) 
        stop("The number of groups does not match the number of contrast coefficients.")
    m1 <- matrix(0, J, nboot)
    m2 <- 1
    mval <- 1
    set.seed(2)
    for (j in 1:J) {
        mval[j] <- est(x[[j]], ...)
        xcen <- x[[j]] - est(x[[j]], ...)
        data <- matrix(sample(xcen, size = length(x[[j]]) * nboot, 
            replace = TRUE), nrow = nboot)
        m1[j, ] <- apply(data, 1, est, ...)
        m2[j] <- var(m1[j, ])
    }
    boot <- matrix(0, ncol(con), nboot)
    bot <- 1
    for (d in 1:ncol(con)) {
        top <- apply(m1, 2, trimpartt, con[, d])
        consq <- con[, d]^2
        bot[d] <- trimpartt(m2, consq)
        boot[d, ] <- abs(top)/sqrt(bot[d])
    }
    testb <- apply(boot, 2, max)
    ic <- floor((1 - alpha) * nboot)
    testb <- sort(testb)
    psihat <- matrix(0, ncol(con), 6)
    dimnames(psihat) <- list(NULL, c("con.num", "psihat", "ci.lower", 
        "ci.upper", "se", "p.value"))
    for (d in 1:ncol(con)) {
        psihat[d, 1] <- d
        psihat[d, 2] <- trimpartt(mval, con[, d])
        psihat[d, 3] <- psihat[d, 2] - testb[ic] * sqrt(bot[d])
        psihat[d, 4] <- psihat[d, 2] + testb[ic] * sqrt(bot[d])
        psihat[d, 5] <- sqrt(bot[d])
        pval <- mean((boot[d, ] < abs(psihat[d, 2])/psihat[d, 
            5]))
        psihat[d, 6] <- 1 - pval
    }
    list(psihat = psihat, crit = testb[ic], con = con)
  }

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