run3bo:

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

Usage

run3bo(x, y, fr = 1, est = tmean, theta = 50, phi = 25, nmin = 0, pyhat = FALSE, eout = FALSE, outfun = out, plotit = TRUE, xout = FALSE, nboot = 40, SEED = TRUE, STAND = TRUE, expand = 0.5, scale = FALSE, xlab = "X", ylab = "Y", zlab = "", ticktype = "simple", ...)

Arguments

x
y
fr
est
theta
phi
nmin
pyhat
eout
outfun
plotit
xout
nboot
SEED
STAND
expand
scale
xlab
ylab
zlab
ticktype
...

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, theta = 50, phi = 25, nmin = 0, 
    pyhat = FALSE, eout = FALSE, outfun = out, plotit = TRUE, 
    xout = FALSE, nboot = 40, SEED = TRUE, STAND = TRUE, expand = 0.5, 
    scale = FALSE, xlab = "X", ylab = "Y", zlab = "", ticktype = "simple", 
    ...) 
{
    library(MASS)
    library(akima)
    if (SEED) 
        set.seed(2)
    temp <- cbind(x, y)
    x <- as.matrix(x)
    p <- ncol(x)
    p1 <- p + 1
    if (p > 2) 
        plotit <- F
    temp <- elimna(temp)
    x <- temp[, 1:p]
    x <- as.matrix(x)
    y <- temp[, p1]
    if (xout) {
        keepit <- rep(T, nrow(x))
        flag <- outfun(x, plotit = FALSE, STAND = STAND, ...)$out.id
        keepit[flag] <- F
        x <- x[keepit, ]
        y <- y[keepit]
    }
    mat <- matrix(NA, nrow = nboot, ncol = length(y))
    vals <- NA
    for (it in 1:nboot) {
        idat <- sample(c(1:length(y)), replace = TRUE)
        xx <- temp[idat, 1:p]
        yy <- temp[idat, p1]
        tmy <- rung3hat(xx, yy, pts = x, est = est, fr = fr, 
            ...)$rmd
        mat[it, ] <- tmy
    }
    rmd <- apply(mat, 2, mean, na.rm = TRUE)
    flag <- !is.na(rmd)
    rmd <- elimna(rmd)
    x <- x[flag, ]
    y <- y[flag]
    nval <- NA
    m <- cov.mve(x)
    for (i in 1:nrow(x)) nval[i] <- length(y[near3d(x, x[i, ], 
        fr, m)])
    if (plotit && ncol(x) == 2) {
        fitr <- rmd[nval > nmin]
        y <- y[nval > nmin]
        x <- x[nval > nmin, ]
        iout <- c(1:length(fitr))
        nm1 <- length(fitr) - 1
        for (i in 1:nm1) {
            ip1 <- i + 1
            for (k in ip1:length(fitr)) if (sum(x[i, ] == x[k, 
                ]) == 2) 
                iout[k] <- 0
        }
        fitr <- fitr[iout >= 1]
        mkeep <- x[iout >= 1, ]
        fit <- interp(mkeep[, 1], mkeep[, 2], fitr)
        persp(fit, theta = theta, phi = phi, xlab = xlab, ylab = ylab, 
            zlab = zlab, expand = expand, scale = scale, ticktype = ticktype)
    }
    last <- "Done"
    if (pyhat) 
        last <- rmd
    list(output = last)
  }

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