reg1mcp:

Usage Arguments Examples

Usage

1
reg1mcp(x, y, regfun = tsreg, SEED = TRUE, nboot = 100, xout = FALSE, outfun = outpro, STAND = TRUE, alpha = 0.05, pr = TRUE, MC = FALSE, ...)

Arguments

x
y
regfun
SEED
nboot
xout
outfun
STAND
alpha
pr
MC
...

Examples

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
##---- 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, regfun = tsreg, SEED = TRUE, nboot = 100, xout = FALSE, 
    outfun = outpro, STAND = TRUE, alpha = 0.05, pr = TRUE, MC = FALSE, 
    ...) 
{
    if (SEED) 
        set.seed(2)
    if (!is.list(x)) 
        stop("Argument x should have list mode")
    if (!is.list(y)) 
        stop("Argument y should have list mode")
    J = length(x)
    x = lapply(x, as.matrix)
    pchk = lapply(x, ncol)
    temp = matl(pchk)
    if (var(as.vector(temp)) != 0) 
        stop("Something is wrong. Number of covariates differs among the groups being compared")
    nv = NULL
    p = ncol(x[[1]])
    p1 = p + 1
    for (j in 1:J) {
        xy = elimna(cbind(x[[j]], y[[j]]))
        x[[j]] = xy[, 1:p]
        y[[j]] = xy[, p1]
        x[[j]] = as.matrix(x[[j]])
        nv = c(nv, nrow(x[[j]]))
    }
    nv.keep = nv
    critrad = NULL
    if (xout) {
        temp = lapply(x, outfun, plotit = FALSE, STAND = STAND, 
            ...)
        for (j in 1:J) {
            x[[j]] = x[[j]][temp[[j]]$keep, ]
            y[[j]] = y[[j]][temp[[j]]$keep]
            nv.keep[j] = length(y[[j]])
        }
    }
    tot = (J^2 - J)/2
    dvec <- alpha/c(1:tot)
    outl = list()
    nr = tot * p1
    outp = matrix(NA, ncol = 7, nrow = nr)
    x = lapply(x, as.matrix)
    rlab = rep("Intercept", tot)
    xx = list()
    yy = list()
    iall = 0
    ivp = c(1, tot) - tot
    for (ip in 1:p) {
        rlab = c(rlab, rep(paste("slope", ip), tot))
    }
    i = 0
    sk = 1 + tot * p
    st = seq(1, sk, tot)
    st = st - 1
    for (j in 1:J) {
        for (k in 1:J) {
            if (j < k) {
                i = i + 1
                st = st + 1
                xx[[1]] = x[[j]][, 1:p]
                xx[[2]] = x[[k]][, 1:p]
                yy[[1]] = y[[j]]
                yy[[2]] = y[[k]]
                if (!MC) 
                  temp = reg2ci(xx[[1]], yy[[1]], xx[[2]], yy[[2]], 
                    regfun = regfun)$output
                if (MC) 
                  temp = reg2ci(xx[[1]], yy[[1]], xx[[2]], yy[[2]], 
                    regfun = regfun)$output
                iall = iall + 1
                outp[iall, 1] = j
                outp[iall, 2] = k
                outp[st, 3] = temp[, 4]
                outp[st, 5] = temp[, 2]
                outp[st, 6] = temp[, 3]
            }
        }
    }
    for (i in 1:p1) {
        ivp = ivp + tot
        temp2 <- order(0 - outp[ivp[1]:ivp[2], 3])
        icc = c(ivp[1]:ivp[2])
        icc[temp2] = dvec
        outp[ivp[1]:ivp[2], 4] = icc
    }
    flag = (outp[, 3] <= outp[, 4])
    outp[, 7] = rep(0, nr)
    outp[flag, 7] = 1
    v = outp[1:tot, 1]
    vall = rep(v, p1)
    outp[, 1] = vall
    v = outp[1:tot, 2]
    vall = rep(v, p1)
    outp[, 2] = vall
    dimnames(outp) = list(rlab, c("Group", "Group", "p.value", 
        "p.crit", "ci.low", "ci.hi", "Sig"))
    list(n = nv, n.keep = nv.keep, output = outp)
  }

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