runm3d:

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

Usage

runm3d(x, y, theta = 50, phi = 25, fr = 0.8, tr = 0.2, plotit = TRUE, pyhat = FALSE, nmin = 0, expand = 0.5, scale = FALSE, zscale = FALSE, xout = FALSE, outfun = out, eout = FALSE, xlab = "X", ylab = "Y", zlab = "", pr = TRUE, SEED = TRUE, ticktype = "simple")

Arguments

x
y
theta
phi
fr
tr
plotit
pyhat
nmin
expand
scale
zscale
xout
outfun
eout
xlab
ylab
zlab
pr
SEED
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, theta = 50, phi = 25, fr = 0.8, tr = 0.2, plotit = TRUE, 
    pyhat = FALSE, nmin = 0, expand = 0.5, scale = FALSE, zscale = FALSE, 
    xout = FALSE, outfun = out, eout = FALSE, xlab = "X", ylab = "Y", 
    zlab = "", pr = TRUE, SEED = TRUE, ticktype = "simple") 
{
    library(MASS)
    library(akima)
    if (plotit) {
        if (pr) {
            print("Note: when there is independence, scale=F is probably best")
            print("When there is dependence, scale=T is probably best")
        }
    }
    if (!is.matrix(x)) 
        stop("x should be a matrix")
    if (nrow(x) != length(y)) 
        stop("number of rows of x should equal length of y")
    temp <- cbind(x, y)
    p <- ncol(x)
    p1 <- p + 1
    temp <- elimna(temp)
    if (xout) {
        keepit <- rep(T, nrow(x))
        flag <- outfun(x, plotit = FALSE)$out.id
        keepit[flag] <- F
        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]
    pyhat <- as.logical(pyhat)
    plotit <- as.logical(plotit)
    if (SEED) 
        set.seed(12)
    m <- cov.mve(x)
    iout <- c(1:nrow(x))
    rmd <- 1
    nval <- 1
    for (i in 1:nrow(x)) rmd[i] <- mean(y[near3d(x, x[i, ], fr, 
        m)], tr)
    for (i in 1:nrow(x)) nval[i] <- length(y[near3d(x, x[i, ], 
        fr, m)])
    if (plotit) {
        if (ncol(x) != 2) 
            stop("When plotting, x must be an n by 2 matrix")
        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
    last
  }

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