# NOT RUN {
# For the 1-of-3 rule with r=20 future sampling occasions, look at the
# relationship between confidence level and sample size for a one-sided
# upper simultaneous nonparametric prediction interval.
dev.new()
plotPredIntNparSimultaneousDesign(k = 1, m = 3, r = 20, range.x.var = c(2, 20))
#==========
# Plot confidence level vs. sample size for various values of number of
# future sampling occasions (r):
dev.new()
plotPredIntNparSimultaneousDesign(m = 3, r = 10, rule = "CA",
ylim = c(0, 1), main = "")
plotPredIntNparSimultaneousDesign(m = 3, r = 20, rule = "CA", add = TRUE,
plot.col = "red")
plotPredIntNparSimultaneousDesign(m = 3, r = 30, rule = "CA", add = TRUE,
plot.col = "blue")
legend("bottomright", c("r=10", "r=20", "r=30"), lty = 1, lwd = 3 * par("cex"),
col = c("black", "red", "blue"), bty = "n")
title(main = paste("Confidence Level vs. Sample Size for Simultaneous",
"Nonparametric PI with Various Values of r", sep="\n"))
#==========
# Modifying Example 19-5 of USEPA (2009, p. 19-33), plot confidence level
# versus sample size (number of background observations requried) for
# a 1-of-3 plan assuming r = 10 compliance wells (future sampling occasions).
dev.new()
plotPredIntNparSimultaneousDesign(k = 1, m = 3, r = 10, rule = "k.of.m")
#==========
# Clean up
#---------
graphics.off()
# }
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