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

Usage Arguments Examples

outpca(x, cor = TRUE, loadings = TRUE, covlist = NULL, scree = TRUE, SCORES = FALSE, ALL = TRUE, pval = NULL, cop = 3, ADJ = FALSE, SEED = TRUE, pr = TRUE, STAND = TRUE, xlab = "Principal Component", ylab = "Proportion of Variance", ...)

`x`
`cor`
`loadings`
`covlist`
`scree`
`SCORES`
`ALL`
`pval`
`cop`
`ADJ`
`SEED`
`pr`
`STAND`
`xlab`
`ylab`
`...`

##---- 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, cor = TRUE, loadings = TRUE, covlist = NULL, scree = TRUE, 
    SCORES = FALSE, ALL = TRUE, pval = NULL, cop = 3, ADJ = FALSE, 
    SEED = TRUE, pr = TRUE, STAND = TRUE, xlab = "Principal Component", 
    ylab = "Proportion of Variance", ...) 
{
    x <- elimna(x)
    m <- ncol(x)
    if (m > 9) {
        if (pr) 
            print("With more than 9 variables, might want to use ADJ=T")
    }
    if (!ADJ) 
        flag <- outpro(x, cop = cop, STAND = STAND)$keep
    if (ADJ) 
        flag <- outproad(x, cop = cop, SEED = SEED, STAND = STAND)$results$keep
    remx <- x
    temp2 <- princomp(remx)
    x <- x[flag, ]
    loc <- apply(x, 2, mean)
    temp <- princomp(x, cor = cor, scores = TRUE, covlist = covlist)
    if (scree) {
        z = temp$sdev
        pv = z^2
        cs = pv/sum(pv)
        cm = cumsum(cs)
        plot(rep(c(1:ncol(x)), 2), c(cs, cm), type = "n", xlab = xlab, 
            ylab = ylab)
        points(c(1:ncol(x)), cs, pch = "*")
        lines(c(1:ncol(x)), cs, lty = 1)
        points(c(1:ncol(x)), cm, pch = ".")
        lines(c(1:ncol(x)), cm, lty = 2)
    }
    if (!SCORES) 
        temp <- summary(temp, loadings = loadings)
    if (SCORES) {
        if (is.null(pval)) 
            stop("When computing scores, specify pval, number of components")
        if (!ALL) 
            temp <- temp$scores[, 1:pval]
        if (ALL) {
            temp <- summary(temp, loadings = T)
            B <- temp[2]$loadings[1:m, 1:m]
            z <- remx
            for (i in 1:nrow(z)) z[i, ] <- z[i, ] - loc
            temp <- t(B) %*% t(z)
            temp <- t(temp)
            temp <- temp[, 1:pval]
        }
    }
    temp
  }