Ppca:

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

Usage

Ppca(x, p = ncol(x) - 1, locfun = L1medcen, loc.val = NULL, SCORES = FALSE, gvar.fun = cov.mba, pr = TRUE, SEED = TRUE, gcov = rmba, SCALE = TRUE, ...)

Arguments

x
p
locfun
loc.val
SCORES
gvar.fun
pr
SEED
gcov
SCALE
...

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, p = ncol(x) - 1, locfun = L1medcen, loc.val = NULL, 
    SCORES = FALSE, gvar.fun = cov.mba, pr = TRUE, SEED = TRUE, 
    gcov = rmba, SCALE = TRUE, ...) 
{
    x = as.matrix(x)
    x <- elimna(x)
    n <- nrow(x)
    m <- ncol(x)
    xdat = c(n, m, p, as.vector(x))
    if (!SCALE) {
        if (is.null(loc.val)) 
            info <- locfun(x, ...)$center
        if (!is.null(loc.val)) 
            info <- loc.val
        for (i in 1:n) x[i, ] <- x[i, ] - info
    }
    if (SCALE) {
        ms = gcov(x)
        for (i in 1:n) x[i, ] <- x[i, ] - ms$center
        for (j in 1:m) x[, j] <- x[, j]/sqrt(ms$cov[j, j])
    }
    vals <- NA
    z <- matrix(nrow = n, ncol = p)
    np = p * m
    B = robpca(x, pval = p, plotit = FALSE, pr = pr, SEED = SEED, 
        scree = FALSE)$P
    B = t(B)
    Bs = nelderv2(xdat, np, NMpca, START = B)
    Bop = matrix(Bs, nrow = p, ncol = m)
    Bop = t(ortho(t(Bop)))
    z <- matrix(nrow = n, ncol = p)
    zval <- NULL
    for (i in 1:n) z[i, ] <- Bop %*% as.matrix(x[i, ])
    if (SCORES) 
        zval <- z
    val = gvarg(z)
    list(B = Bop, gen.sd = sqrt(val), scores = zval)
  }

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