mbalata:

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

Usage

mbalata(x, y, k = 6, nsamp = 7)

Arguments

x
y
k
nsamp

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, y, k = 6, nsamp = 7) 
{
    x <- as.matrix(x)
    n <- dim(x)[1]
    q <- dim(x)[2]
    vals <- c(q + 3 + floor(n/100), q + 3 + floor(n/40), q + 
        3 + floor(n/20), q + 3 + floor(n/10), q + 3 + floor(n/5), 
        q + 3 + floor(n/3), q + 3 + floor(n/2))
    covv <- diag(q)
    centers <- sample(n, nsamp)
    temp <- lsfit(x, y)
    mbaf <- temp$coef
    res <- temp$residuals
    crit <- k^2 * median(res^2)
    cn <- sum(res^2 <= crit)
    absres <- sort(abs(res))
    critf <- sum(absres[1:cn])
    for (i in 1:nsamp) {
        md2 <- mahalanobis(x, center = x[centers[i], ], covv)
        smd2 <- sort(md2)
        for (j in 1:7) {
            temp <- lsfit(x[md2 <= smd2[vals[j]], ], y[md2 <= 
                smd2[vals[j]]])
            res <- y - temp$coef[1] - x %*% temp$coef[-1]
            crit <- k^2 * median(res^2)
            cn <- sum(res^2 <= crit)
            absres <- sort(abs(res))
            crit <- sum(absres[1:cn])
            if (crit < critf) {
                critf <- crit
                mbaf <- temp$coef
            }
        }
    }
    list(coef = mbaf, critf = critf)
  }

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