regYvar:

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

Usage

regYvar(x, y, regfun = tsreg, pts = x, nboot = 100, xout = FALSE, outfun = out, SEED = TRUE, ...)

Arguments

x
y
regfun
pts
nboot
xout
outfun
SEED
...

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, regfun = tsreg, pts = x, nboot = 100, xout = FALSE, 
    outfun = out, SEED = TRUE, ...) 
{
    xy = elimna(cbind(x, y))
    x <- as.matrix(x)
    p = ncol(x)
    p1 = p + 1
    vals = NA
    x <- xy[, 1:p]
    y <- xy[, p1]
    if (xout) {
        m <- cbind(x, y)
        flag <- outfun(x, plotit = FALSE, ...)$keep
        m <- m[flag, ]
        x <- m[, 1:p]
        y <- m[, p1]
    }
    nv = length(y)
    x <- as.matrix(x)
    pts = as.matrix(pts)
    nvpts = nrow(pts)
    bvec = matrix(NA, nrow = nboot, ncol = nvpts)
    if (SEED) 
        set.seed(2)
    data <- matrix(sample(length(y), size = length(y) * nboot, 
        replace = TRUE), nrow = nboot)
    for (ib in 1:nboot) {
        bvec[ib, ] = regYsub(x[data[ib, ], ], y[data[ib, ]], 
            xr = pts, p1 = p1, regfun = regfun, ...)
    }
    sqsd = apply(bvec, 2, var)
    sqsd
  }

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