spmcpb:

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

Usage

spmcpb(J, K, x, est = tmean, JK = J * K, grp = c(1:JK), dif = TRUE, alpha = 0.05, nboot = NA, pr = TRUE, ...)

Arguments

J
K
x
est
JK
grp
dif
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 (J, K, x, est = tmean, JK = J * K, grp = c(1:JK), dif = TRUE, 
    alpha = 0.05, nboot = NA, pr = TRUE, ...) 
{
    if (is.matrix(x)) {
        y <- list()
        for (j in 1:ncol(x)) y[[j]] <- x[, j]
        x <- y
    }
    if (pr) 
        print("As of Sept. 2005, est defaults to tmean")
    JK <- J * K
    data <- list()
    for (j in 1:length(x)) {
        data[[j]] <- x[[grp[j]]]
    }
    x <- data
    jp <- 1 - K
    kv <- 0
    kv2 <- 0
    for (j in 1:J) {
        jp <- jp + K
        xmat <- matrix(NA, ncol = K, nrow = length(x[[jp]]))
        for (k in 1:K) {
            kv <- kv + 1
            xmat[, k] <- x[[kv]]
        }
        xmat <- elimna(xmat)
        for (k in 1:K) {
            kv2 <- kv2 + 1
            x[[kv2]] <- xmat[, k]
        }
    }
    xx <- x
    set.seed(2)
    nvec <- NA
    jp <- 1 - K
    for (j in 1:J) {
        jp <- jp + K
        nvec[j] <- length(x[[jp]])
    }
    x <- matrix(NA, nrow = nvec[1], ncol = K)
    for (k in 1:K) x[, k] <- xx[[k]]
    kc <- K
    for (j in 2:J) {
        temp <- matrix(NA, nrow = nvec[j], ncol = K)
        for (k in 1:K) {
            kc <- kc + 1
            temp[, k] <- xx[[kc]]
            x <- rbind(x, temp)
        }
    }
    temp <- rmmcppb(x, est = est, nboot = nboot, dif = dif, alpha = alpha, 
        plotit = FALSE, ...)
    list(output = temp$output, con = temp$con, num.sig = temp$num.sig)
  }

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