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

Usage Arguments Examples

kerreg(x, y, pyhat = FALSE, pts = NA, plotit = TRUE, theta = 50, phi = 25, expand = 0.5, scale = FALSE, zscale = FALSE, eout = FALSE, xout = FALSE, outfun = out, np = 100, xlab = "X", ylab = "Y", zlab = "Z", varfun = pbvar, e.pow = TRUE, pr = TRUE, ticktype = "simple", pch = ".", ...)

`x`
`y`
`pyhat`
`pts`
`plotit`
`theta`
`phi`
`expand`
`scale`
`zscale`
`eout`
`xout`
`outfun`
`np`
`xlab`
`ylab`
`zlab`
`varfun`
`e.pow`
`pr`
`ticktype`
`pch`
`...`

##---- 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, pyhat = FALSE, pts = NA, plotit = TRUE, theta = 50, 
    phi = 25, expand = 0.5, scale = FALSE, zscale = FALSE, eout = FALSE, 
    xout = FALSE, outfun = out, np = 100, xlab = "X", ylab = "Y", 
    zlab = "Z", varfun = pbvar, e.pow = TRUE, pr = TRUE, ticktype = "simple", 
    pch = ".", ...) 
{
    library(akima)
    x <- as.matrix(x)
    xx <- cbind(x, y)
    xx <- elimna(xx)
    x <- xx[, 1:ncol(x)]
    x <- as.matrix(x)
    y <- xx[, ncol(x) + 1]
    d <- ncol(x)
    np1 <- d + 1
    m <- elimna(cbind(x, y))
    if (xout && eout) 
        stop("Can't have eout=xout=T")
    if (eout) {
        flag <- outfun(m, plotit = FALSE, ...)$keep
        m <- m[flag, ]
    }
    if (xout) {
        flag <- outfun(x, plotit = FALSE, ...)$keep
        m <- m[flag, ]
    }
    if (zscale) {
        for (j in 1:np1) {
            m[, j] <- (m[, j] - median(m[, j]))/mad(m[, j])
        }
    }
    x <- m[, 1:d]
    x <- as.matrix(x)
    y <- m[, np1]
    n <- nrow(x)
    if (d > 1) {
        xrem <- x
        pi <- gamma(0.5)^2
        cd <- c(2, pi)
        if (d == 2) 
            A <- 1.77
        if (d == 3) 
            A <- 2.78
        if (d > 2) {
            for (j in 3:d) cd[j] <- 2 * pi * cd[j - 2]/j
        }
        if (d > 3) 
            A <- (8 * d * (d + 2) * (d + 4) * (2 * sqrt(pi))^d)/((2 * 
                d + 1) * cd[d])
        hval <- A * (1/n)^(1/(d + 4))
        for (j in 1:d) {
            sig <- sqrt(var(x[, j]))
            temp <- idealf(x[, j])
            iqr <- (temp$qu - temp$ql)/1.34
            A <- min(c(sig, iqr))
            x[, j] <- x[, j]/A
        }
        xx <- cbind(rep(1, nrow(x)), x)
        yhat <- NA
        for (j in 1:n) {
            yhat[j] <- NA
            temp1 <- t(t(x) - x[j, ])/(hval)
            temp1 <- temp1^2
            temp1 <- apply(temp1, 1, FUN = "sum")
            temp <- 0.5 * (d + 2) * (1 - temp1)/cd[d]
            epan <- ifelse(temp1 < 1, temp, 0)
            chkit <- sum(epan != 0)
            if (chkit >= np1) {
                vals <- lsfit(x, y, wt = epan)$coef
                yhat[j] <- xx[j, ] %*% vals
            }
        }
        if (plotit && d == 2) {
            if (pr) {
                if (!scale) {
                  print("scale=F is specified")
                  print("If there is dependence, might use scale=T")
                }
            }
            m <- elimna(cbind(xrem, yhat))
            xrem <- m[, 1:d]
            yhat <- m[, np1]
            fitr <- yhat
            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(xrem[i, ] == 
                  xrem[k, ]) == 2) 
                  iout[k] <- 0
            }
            fitr <- fitr[iout >= 1]
            mkeep <- xrem[iout >= 1, ]
            fit <- interp(mkeep[, 1], mkeep[, 2], fitr)
            persp(fit, theta = theta, phi = phi, expand = expand, 
                xlab = xlab, ylab = ylab, zlab = zlab, scale = scale, 
                ticktype = ticktype)
        }
    }
    if (d == 1) {
        yhat <- locreg(x[, 1], y, pyhat = TRUE, np = np, plotit = plotit, 
            pts = pts, xlab = xlab, ylab = ylab, pch = pch)
        yhat2 <- locreg(x[, 1], y, pyhat = TRUE, np = 0, plotit = FALSE)
    }
    if (d > 1) 
        yhat2 <- yhat
    m <- NULL
    if (pyhat) 
        m <- yhat
    m
  }