r1mcp:

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

Usage

r1mcp(x, alpha = 0.05, bhop = FALSE)

Arguments

x
alpha
bhop

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, bhop = FALSE) 
{
    if (is.matrix(x)) 
        x <- listm(x)
    if (!is.list(x)) 
        stop("Data must be stored in list mode or a matrix.")
    J <- length(x)
    for (j in 1:J) {
        xx <- x[[j]]
        x[[j]] <- xx[!is.na(xx)]
    }
    CC <- (J^2 - J)/2
    ncon <- CC
    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
    output <- matrix(0, CC, 5)
    dimnames(output) <- list(NULL, c("Level", "Level", "test.stat", 
        "p.value", "p.crit"))
    ic <- 0
    for (j in 1:J) {
        for (jj in 1:J) {
            if (j < jj) {
                ic <- ic + 1
                output[ic, 1] <- j
                output[ic, 2] <- jj
                temp <- bdm(x[c(j, jj)])
                output[ic, 3] <- temp$output$F
                output[ic, 4] <- temp$output$sig
            }
        }
    }
    temp2 <- order(0 - output[, 4])
    output[temp2, 5] <- dvec[1:length(temp2)]
    list(output = output)
  }

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