tbscov:

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

Usage

tbscov(x, eps = 0.001, maxiter = 20, r = 0.45, alpha = 0.05)

Arguments

x
eps
maxiter
r
alpha

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, eps = 0.001, maxiter = 20, r = 0.45, alpha = 0.05) 
{
    if (!is.matrix(x)) 
        stop("x should be a matrix with two or more columns")
    x <- elimna(x)
    library(MASS)
    temp <- cov.mve(x)
    t1 <- temp$center
    s <- temp$cov
    n <- nrow(x)
    p <- ncol(x)
    if (p == 1) 
        stop("x should be a matrix with two or more columns")
    c1M <- cgen.bt(n, p, r, alpha, asymp = FALSE)
    c1 <- c1M$c1
    if (c1 == 0) 
        c1 <- 0.001
    M <- c1M$M
    b0 <- erho.bt(p, c1, M)
    crit <- 100
    iter <- 1
    w1d <- rep(1, n)
    w2d <- w1d
    while ((crit > eps) & (iter <= maxiter)) {
        t.old <- t1
        s.old <- s
        wt.old <- w1d
        v.old <- w2d
        d2 <- mahalanobis(x, center = t1, cov = s)
        d <- sqrt(d2)
        k <- ksolve.bt(d, p, c1, M, b0)
        d <- d/k
        w1d <- wt.bt(d, c1, M)
        w2d <- v.bt(d, c1, M)
        t1 <- (w1d %*% x)/sum(w1d)
        s <- s * 0
        for (i in 1:n) {
            xc <- as.vector(x[i, ] - t1)
            s <- s + as.numeric(w1d[i]) * (xc %o% xc)
        }
        s <- p * s/sum(w2d)
        mnorm <- sqrt(as.vector(t.old) %*% as.vector(t.old))
        snorm <- eigen(s.old)$values[1]
        crit1 <- max(abs(t1 - t.old))
        crit <- max(abs(w1d - wt.old))/max(w1d)
        iter <- iter + 1
    }
    s
  }

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