runpd:

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

Usage

runpd(x, y, pts = x, est = tmean, fr = 0.8, plotit = TRUE, pyhat = FALSE, nmin = 0, scale = TRUE, expand = 0.5, xout = FALSE, outfun = out, pr = TRUE, xlab = "X1", ylab = "X2", zlab = "", LP = TRUE, theta = 50, phi = 25, duplicate = "error", MC = FALSE, ticktype = "simple", ...)

Arguments

x
y
pts
est
fr
plotit
pyhat
nmin
scale
expand
xout
outfun
pr
xlab
ylab
zlab
LP
theta
phi
duplicate
MC
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, pts = x, est = tmean, fr = 0.8, plotit = TRUE, 
    pyhat = FALSE, nmin = 0, scale = TRUE, expand = 0.5, xout = FALSE, 
    outfun = out, pr = TRUE, xlab = "X1", ylab = "X2", zlab = "", 
    LP = TRUE, theta = 50, phi = 25, duplicate = "error", MC = FALSE, 
    ticktype = "simple", ...) 
{
    if (is.list(x)) 
        stop("Data should  not stored be stored in list mode")
    x <- as.matrix(x)
    pval <- ncol(x)
    xx <- cbind(x, y)
    xx <- elimna(xx)
    x <- xx[, 1:pval]
    x <- as.matrix(x)
    y <- xx[, pval + 1]
    if (xout) {
        keepit <- outfun(x, plotit = FALSE)$keep
        x <- x[keepit, ]
        y <- y[keepit]
    }
    plotit <- as.logical(plotit)
    iout <- c(1:nrow(x))
    rmd <- 1
    nval <- 1
    nmat <- pdclose(x, pts, fr = fr, MC = MC)
    for (i in 1:nrow(pts)) rmd[i] <- est(y[nmat[i, ]], ...)
    for (i in 1:nrow(pts)) nval[i] <- sum(nmat[i, ])
    if (ncol(x) == 2) {
        if (plotit) {
            library(akima)
            fitr <- rmd[nval > nmin]
            y <- y[nval > nmin]
            x <- x[nval > nmin, ]
            iout <- c(1:length(fitr))
            nm1 <- length(fitr) - 1
            for (i in 1:nm1) {
                ip1 <- i + 1
                for (k in ip1:length(fitr)) if (sum(x[i, ] == 
                  x[k, ]) == 2) 
                  iout[k] <- 0
            }
            if (plotit) {
                if (pr) {
                  if (!scale) 
                    print("With dependence, suggest using scale=T")
                }
                fitr <- rmd[nval > nmin]
                iout <- c(1:length(fitr))
                nm1 <- length(fitr) - 1
                for (i in 1:nm1) {
                  ip1 <- i + 1
                  for (k in ip1:length(fitr)) if (sum(x[i, ] == 
                    x[k, ]) == 2) 
                    iout[k] <- 0
                }
                fitr <- fitr[iout >= 1]
                mkeep <- x[iout >= 1, ]
                if (LP) 
                  fitr = lplot(x[iout >= 1, ], fitr, pyhat = TRUE, 
                    pr = FALSE, plotit = FALSE)$yhat
                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
  }

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