SMpre:

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

Usage

SMpre(x, y, est = tmean, fr = NA, varfun = pbvar, model = NULL, adz = TRUE, xout = FALSE, outfun = out, ...)

Arguments

x
y
est
fr
varfun
model
adz
xout
outfun
...

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, est = tmean, fr = NA, varfun = pbvar, model = NULL, 
    adz = TRUE, xout = FALSE, outfun = out, ...) 
{
    if (xout) {
        x <- as.matrix(x)
        flag <- outfun(x, ...)$keep
        x <- x[flag, ]
        y <- y[flag]
    }
    x = as.matrix(x)
    p = ncol(x)
    if (p > 5) 
        stop("Can have at most 5 predictors")
    if (is.null(model)) 
        model = modgen(p)
    mout <- matrix(NA, length(model), 3, dimnames = list(NULL, 
        c("error", "var.used", "rank")))
    for (imod in 1:length(model)) {
        nmod = length(model[[imod]]) - 1
        temp = c(nmod:0)
        mout[imod, 2] = sum(model[[imod]] * 10^temp)
        mout[imod, 1] = rplotCV(x[, model[[imod]]], y, fr = fr, 
            est = est, varfun = varfun)$VAR.Y.HAT
    }
    if (adz) {
        va = 0
        for (i in 1:30) va[i] = y[i] - tmean(y[-i])
        no = pbvar(va)
        mout = rbind(mout, c(no, 0, NA))
    }
    mout[, 3] = rank(mout[, 1])
    list(estimates = mout)
  }

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