rslopesm:

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

Usage

rslopesm(x, y, fr = 1, est = tmean, nmin = 10, pts = x, plotit = FALSE, xlab = "X", ylab = "Y", SEED = TRUE, nboot = 40, xout = FALSE, RNA = TRUE, atr = 0.2, scat = TRUE, pyhat = TRUE, ...)

Arguments

x
y
fr
est
nmin
pts
plotit
xlab
ylab
SEED
nboot
xout
RNA
atr
scat
pyhat
...

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, fr = 1, est = tmean, nmin = 10, pts = x, plotit = FALSE, 
    xlab = "X", ylab = "Y", SEED = TRUE, nboot = 40, xout = FALSE, 
    RNA = TRUE, atr = 0.2, scat = TRUE, pyhat = TRUE, ...) 
{
    if (SEED) 
        set.seed(2)
    temp <- cbind(x, y)
    if (ncol(temp) != 2) 
        stop("One predictor only is allowed")
    temp <- elimna(temp)
    if (xout) {
        flag <- outfun(temp[, 1], plotit = FALSE)$keep
        temp <- temp[flag, ]
        x <- temp[, 1]
        y <- temp[, 2]
    }
    flag <- order(x)
    x <- x[flag]
    y <- y[flag]
    mat <- matrix(NA, nrow = nboot, ncol = length(pts))
    vals <- NA
    for (it in 1:nboot) {
        idat <- sample(c(1:length(y)), replace = T)
        xx <- temp[idat, 1]
        yy <- temp[idat, 2]
        mat[it, ] <- rslope(xx, yy, fr = fr, est = est, nmin = nmin, 
            pts = x, plotit = FALSE)
    }
    rmd <- apply(mat, 2, mean, na.rm = RNA, tr = atr)
    flag <- is.na(rmd)
    rmdsm <- lplot(x, rmd, pyhat = TRUE, plotit = plotit)
    output <- "Done"
    if (pyhat) {
        temp <- rep(NA, length(x))
        temp[!flag] <- rmdsm$yhat.values
        output <- temp
    }
    output
  }

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