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

Usage Arguments Examples

anclin(x1, y1, x2, y2, regfun = tsreg, pts = NULL, ALL = FALSE, npts = 25, plotit = TRUE, SCAT = TRUE, pch1 = "*", pch2 = "+", nboot = 100, ADJ = TRUE, xout = FALSE, outfun = out, SEED = TRUE, p.crit = 0.015, alpha = 0.05, crit = NULL, null.value = 0, plotPV = FALSE, scale = TRUE, span = 0.75, xlab = "X", xlab1 = "X1", xlab2 = "X2", ylab = "p-values", ylab2 = "Y", theta = 50, phi = 25, MC = FALSE, nreps = 1000, pch = "*", ...)

`x1`
`y1`
`x2`
`y2`
`regfun`
`pts`
`ALL`
`npts`
`plotit`
`SCAT`
`pch1`
`pch2`
`nboot`
`ADJ`
`xout`
`outfun`
`SEED`
`p.crit`
`alpha`
`crit`
`null.value`
`plotPV`
`scale`
`span`
`xlab`
`xlab1`
`xlab2`
`ylab`
`ylab2`
`theta`
`phi`
`MC`
`nreps`
`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 (x1, y1, x2, y2, regfun = tsreg, pts = NULL, ALL = FALSE, 
    npts = 25, plotit = TRUE, SCAT = TRUE, pch1 = "*", pch2 = "+", 
    nboot = 100, ADJ = TRUE, xout = FALSE, outfun = out, SEED = TRUE, 
    p.crit = 0.015, alpha = 0.05, crit = NULL, null.value = 0, 
    plotPV = FALSE, scale = TRUE, span = 0.75, xlab = "X", xlab1 = "X1", 
    xlab2 = "X2", ylab = "p-values", ylab2 = "Y", theta = 50, 
    phi = 25, MC = FALSE, nreps = 1000, pch = "*", ...) 
{
    xy = elimna(cbind(x1, y1))
    x1 <- as.matrix(x1)
    p = ncol(x1)
    if (p > 1) 
        stop("Current version allows one covariate only")
    p1 = p + 1
    vals = NA
    x1 <- xy[, 1:p]
    y1 <- xy[, p1]
    x1 <- as.matrix(x1)
    xy = elimna(cbind(x2, y2))
    x2 <- as.matrix(x2)
    p = ncol(x2)
    p1 = p + 1
    vals = NA
    x2 <- xy[, 1:p]
    y2 <- xy[, p1]
    x2 <- as.matrix(x2)
    n1 = length(y1)
    n2 = length(y2)
    n = min(c(n1, n2))
    if (xout) {
        m <- cbind(x1, y1)
        flag <- outfun(x1, plotit = FALSE, ...)$keep
        m <- m[flag, ]
        n1 = nrow(m)
        x1 <- m[, 1:p]
        y1 <- m[, p1]
        x1 = as.matrix(x1)
        m <- cbind(x2, y2)
        flag <- outfun(x2, plotit = FALSE, ...)$keep
        m <- m[flag, ]
        n2 = nrow(m)
        n = min(c(n1, n2))
        x2 <- m[, 1:p]
        y2 <- m[, p1]
        x2 = as.matrix(x2)
    }
    if (is.null(pts)) {
        xall = unique(c(x1, x2))
        if (ALL) 
            pts = xall
        if (!ALL) 
            pts = seq(min(xall), max(xall), length.out = npts)
    }
    if (ADJ) {
        if (n < 10) 
            stop("Should have a sample size of at least 10")
        if (alpha == 0.05) {
            alpha = p.crit
            crit = qnorm(1 - alpha/2)
        }
        if (!ADJ) 
            p.crit = alpha
        if (n < 20 & max(c(n1, n2)) < 100) 
            crit = NULL
        if (p > 1) 
            crit = NULL
    }
    if (is.null(crit) & !ADJ) 
        crit = qnorm(1 - alpha/2)
    if (is.null(crit) & ADJ) {
        if (SEED) 
            set.seed(2)
        padj = regYciCV2G(n1, n2, nboot = nreps, regfun = regfun, 
            MC = MC, SEED = FALSE, ALL = ALL, null.value = null.value, 
            pts = pts, alpha = alpha, ...)$crit.est
        crit = qnorm(1 - padj/2)
        p.crit = padj
    }
    sqsd1 = regYvar(x1, y1, regfun = regfun, pts = pts, nboot = nboot, 
        SEED = SEED)
    sqsd2 = regYvar(x2, y2, regfun = regfun, pts = pts, nboot = nboot, 
        SEED = SEED)
    sd = sqrt(sqsd1 + sqsd2)
    est1 = regYhat(x1, y1, regfun = regfun, xr = pts, ...)
    est2 = regYhat(x2, y2, regfun = regfun, xr = pts, ...)
    pv = 2 * (1 - pnorm(abs(est1 - est2 - null.value)/sd))
    est = cbind(pts, est1 - est2, est1 - est2 - crit * sd, est1 - 
        est2 + crit * sd, pv)
    dimnames(est) = list(NULL, c("X", "Est.Dif", "Lower.ci", 
        "Upper.ci", "p.value"))
    if (plotit) {
        plotPV = FALSE
        plot(c(x1, x2), c(y1, y2), type = "n", xlab = xlab, ylab = ylab2)
        reg1 = regfun(x1, y1, ...)$coef
        reg2 = regfun(x2, y2, ...)$coef
        if (SCAT) {
            points(x1, y1, pch = pch1)
            points(x2, y2, pch = pch2)
        }
        abline(reg1)
        abline(reg2, lty = 2)
    }
    if (plotPV) {
        if (ncol(x1) > 2) 
            stop("Can plot only with one or two independent variables")
        if (ncol(x1) == 1) 
            plot(pts, pv, xlab = xlab, ylab = ylab, pch = pch)
        if (ncol(x2) == 2) 
            lplot(pts, pv, xlab = xlab1, ylab = xlab2, zlab = ylab, 
                span = span, ticktype = "detail", scale = scale, 
                theta = theta, phi = phi)
    }
    list(output = est, p.crit = p.crit, crit.value = crit, num.sig = sum(est[, 
        5] <= p.crit))
  }