Mreglde:

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

Usage

Mreglde(x, y, xout = FALSE, eout = FALSE, outfun = outpro, epow.cov = mcdcov, RES = FALSE, ...)

Arguments

x
y
xout
eout
outfun
epow.cov
RES
...

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, xout = FALSE, eout = FALSE, outfun = outpro, 
    epow.cov = mcdcov, RES = FALSE, ...) 
{
    if (eout) {
        flag = outfun(cbind(x, y), ...)$keep
        x = x[flag, ]
        y = y[flag, ]
    }
    if (xout) {
        flag = outfun(x, ...)$keep
        x = x[flag, ]
        y = y[flag, ]
    }
    npar = (ncol(x) + 1) * ncol(y)
    xy = elimna(cbind(x, y))
    x = xy[, 1:ncol(x)]
    for (i in 1:ncol(x)) x[, i] = (x[, i] - mean(x[, i]))/sqrt(var(x[, 
        i]))
    p1 = ncol(x) + 1
    y = xy[, p1:ncol(xy)]
    INIT = as.vector(lsfit(x, y)$coef)
    xx = c(nrow(x), ncol(x), ncol(y), as.vector(x), as.vector(y))
    Bs = nelderv2(xx, npar, Mreglde.sub, START = INIT)
    Bs = matrix(Bs, ncol = ncol(y))
    dimnames(Bs) <- list(c("INTER", rep("SLOPE", ncol(x))), rep("Y", 
        ncol(Bs)))
    yhat = matrix(NA, nrow = nrow(y), ncol = ncol(y))
    for (i in 1:nrow(y)) {
        z = as.matrix(x[i, ])
        yhat[i, ] = t(Bs[2:nrow(Bs), ]) %*% z
    }
    yhat = yhat + Bs[1, ]
    res = NULL
    if (RES) 
        res = y - yhat
    list(coef = Bs, residuals = res)
  }

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