rung3d:
In musto101/wilcox_R: What the package does (short line)

Usage Arguments Examples

rung3d(x, y, est = onestep, fr = 1, plotit = TRUE, theta = 50, phi = 25, pyhat = FALSE, LP = FALSE, expand = 0.5, scale = FALSE, zscale = TRUE, nmin = 0, xout = FALSE, eout = FALSE, outfun = out, SEED = TRUE, STAND = TRUE, xlab = "X", ylab = "Y", zlab = "", pr = TRUE, duplicate = "error", ticktype = "simple", ...)

`x`
`y`
`est`
`fr`
`plotit`
`theta`
`phi`
`pyhat`
`LP`
`expand`
`scale`
`zscale`
`nmin`
`xout`
`eout`
`outfun`
`SEED`
`STAND`
`xlab`
`ylab`
`zlab`
`pr`
`duplicate`
`ticktype`
`...`

##---- 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 = onestep, fr = 1, plotit = TRUE, theta = 50, 
    phi = 25, pyhat = FALSE, LP = FALSE, expand = 0.5, scale = FALSE, 
    zscale = TRUE, nmin = 0, xout = FALSE, eout = FALSE, outfun = out, 
    SEED = TRUE, STAND = TRUE, xlab = "X", ylab = "Y", zlab = "", 
    pr = TRUE, duplicate = "error", ticktype = "simple", ...) 
{
    library(MASS)
    library(akima)
    if (SEED) 
        set.seed(12)
    if (eout && xout) 
        stop("Not allowed to have eout=xout=T")
    if (!is.matrix(x)) 
        stop("Data are not stored in a matrix.")
    if (nrow(x) != length(y)) 
        stop("Number of rows in x does not match length of y")
    temp <- cbind(x, y)
    p <- ncol(x)
    p1 <- p + 1
    temp <- elimna(temp)
    if (eout) {
        keepit <- outfun(temp, plotit = FALSE)$keep
        x <- x[keepit, ]
        y <- y[keepit]
    }
    if (xout) {
        keepit <- outfun(x, plotit = FALSE, STAND = STAND, ...)$keep
        x <- x[keepit, ]
        y <- y[keepit]
    }
    if (zscale) {
        for (j in 1:p1) {
            temp[, j] <- (temp[, j] - median(temp[, j]))/mad(temp[, 
                j])
        }
    }
    x <- temp[, 1:p]
    y <- temp[, p1]
    m <- cov.mve(x)
    iout <- c(1:nrow(x))
    rmd <- 1
    nval <- 1
    for (i in 1:nrow(x)) rmd[i] <- est(y[near3d(x, x[i, ], fr, 
        m)], ...)
    for (i in 1:nrow(x)) nval[i] <- length(y[near3d(x, x[i, ], 
        fr, m)])
    if (ncol(x) == 2) {
        if (plotit) {
            if (pr) {
                if (!scale) 
                  print("With dependence, suggest using scale=T")
            }
            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]
            if (LP) 
                fitr = lplot(x[iout >= 1, ], fitr, pyhat = TRUE, 
                  pr = FALSE, plotit = FALSE)$yhat
            mkeep <- x[iout >= 1, ]
            fit <- interp(mkeep[, 1], mkeep[, 2], fitr, duplicate = duplicate)
            persp(fit, theta = theta, phi = phi, expand = expand, 
                scale = scale, xlab = xlab, ylab = ylab, zlab = zlab, 
                ticktype = ticktype)
        }
    }
    if (pyhat) 
        last <- rmd
    if (!pyhat) 
        last <- "Done"
    last
  }