Nothing
crm.plot.new <-
function (xx, xname = deparse(substitute(xx)), crm.mean = NULL,
crm.sd = NULL, n.sd = 2, crm.new = 0, ylim = NULL, ...)
{
temp.x <- remove.na(xx)
x <- temp.x$x[1:temp.x$n]
n <- temp.x$n
xmean <- mean(x)
xsd <- sqrt(var(x))
xrsd <- round(100 * xsd/xmean, 2)
xmed <- median(x)
xmad <- mad(x)
rrsd <- round(100 * xmad/xmed, 2)
x.range <- range(x)
cat(" Control Reference Material:", xname, "\n\t\t\t\t Mean =",
signif(xmean, 3), "\t SD =", signif(xsd, 3), "\t RSD% =", xrsd,
"\t N =", n)
cat("\n\t\t\t\tMedian =", signif(xmed, 3), "\tMAD =", signif(xmad, 3),
"\trRSD% =", rrsd, "\n")
#
if(!is.null(crm.mean)) cat(" CRM mean provided =", crm.mean, "\n")
else crm.mean <- xmean
if(!is.null(crm.sd)) cat(" CRM SD provided =", crm.sd, "\n")
else crm.sd <- xsd
cat(" Number of new CRM determinations to be plotted =", crm.new, "\n")
cat(" Number of SDs to be used for tolerance bounds =", n.sd, "\n")
#
hitol <- crm.mean + n.sd * crm.sd
lotol <- crm.mean - n.sd * crm.sd
plot.min <- min(x.range[1], lotol, ylim[1])
plot.max <- max(x.range[2], hitol, ylim[2])
ylabel <- paste(xname, ", red lines indicate \261", n.sd, " SD limits",
sep = "")
#
plot(seq(1:n), x, xlim = c(1, n+crm.new), ylim = c(plot.min, plot.max),
ylab = ylabel, xlab = paste("Ordered determinations of", xname), ...)
abline(h = crm.mean, col = 3, lty = 3)
abline(h = hitol, col = 2, lty = 2)
abline(h = lotol, col = 2, lty = 2)
#
invisible()
}
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