plotCiNparDesign.RdCreate plots involving sample size, quantile, and confidence level for a nonparametric confidence interval for a quantile.
plotCiNparDesign(x.var = "n", y.var = "conf.level", range.x.var = NULL,
n = 25, p = 0.5, conf.level = 0.95, ci.type = "two.sided",
lcl.rank = ifelse(ci.type == "upper", 0, 1),
n.plus.one.minus.ucl.rank = ifelse(ci.type == "lower", 0, 1),
plot.it = TRUE, add = FALSE, n.points = 100, plot.col = "black",
plot.lwd = 3 * par("cex"), plot.lty = 1, digits = .Options$digits,
cex.main = par("cex"), ..., main = NULL, xlab = NULL, ylab = NULL,
type = "l")character string indicating what variable to use for the x-axis.
Possible values are "n" (sample size; the default),
"p" (quantile), and "conf.level" (the confidence level).
character string indicating what variable to use for the y-axis.
Possible values are conf.level (confidence level; the default), and
"n" (sample size).
numeric vector of length 2 indicating the range of the x-variable to use
for the plot. The default value depends on the value of x.var.
When x.var="n" the default value is c(2,50). When
x.var="p" the default value is c(0.5, 0.99).
When x.var="conf.level", the default value is c(0.5, 0.99).
numeric scalar indicating the sample size. The default value is
n=25.
Missing (NA), undefined (NaN), and infinite (Inf, -Inf) values are not allowed.
This argument is ignored if either x.var="n" or y.var="n".
numeric scalar specifying the quantile. The value of this argument must be
between 0 and 1. The default value is p=0.5. The argument is
ignored if x.var="p".
a scalar between 0 and 1 indicating the confidence level associated with the confidence interval.
The default value is conf.level=0.95. This argument is ignored if
x.var="conf.level" or y.var="conf.level".
character string indicating what kind of confidence interval to compute. The
possible values are "two-sided" (the default), "lower", and
"upper".
numeric vectors of non-negative integers indicating the ranks of the
order statistics that are used for the lower and upper bounds of the
confidence interval for the specified quantile(s). When lcl.rank=1
that means use the smallest value as the lower bound, when lcl.rank=2
that means use the second to smallest value as the lower bound, etc.
When n.plus.one.minus.ucl.rank=1 that means use the largest value
as the upper bound, when n.plus.one.minus.ucl.rank=2 that means use
the second to largest value as the upper bound, etc.
A value of 0 for lcl.rank indicates no lower bound
(i.e., -Inf) and a value of
0 for n.plus.one.minus.ucl.rank indicates no upper bound
(i.e., Inf). When ci.type="upper" then lcl.rank is
set to 0 by default, otherwise it is set to 1 by default.
When ci.type="lower" then n.plus.one.minus.ucl.rank is set
to 0 by default, otherwise it is set to 1 by default.
a logical scalar indicating whether to create a plot or add to the
existing plot (see add) on the current graphics device. If
plot.it=FALSE, no plot is produced, but a list of (x,y) values
is returned (see VALUE). The default value is plot.it=TRUE.
a logical scalar indicating whether to add the design plot to the
existing plot (add=TRUE), or to create a plot from scratch
(add=FALSE). The default value is add=FALSE.
This argument is ignored if plot.it=FALSE.
a numeric scalar specifying how many (x,y) pairs to use to produce the plot.
There are n.points x-values evenly spaced between range.x.var[1] and range.x.var[2]. The default value is n.points=100.
a numeric scalar or character string determining the color of the plotted
line or points. The default value is plot.col="black". See the
entry for col in the help file for par
for more information.
a numeric scalar determining the width of the plotted line. The default value is
3*par("cex"). See the entry for lwd in the help file for par
for more information.
a numeric scalar determining the line type of the plotted line. The default value is
plot.lty=1. See the entry for lty in the help file for par
for more information.
a scalar indicating how many significant digits to print out on the plot. The default
value is the current setting of options("digits").
additional graphical parameters (see par).
See the help files for eqnpar, ciNparConfLevel,
and ciNparN for information on how to compute a
nonparametric confidence interval for a quantile, how the confidence level
is computed when other quantities are fixed, and how the sample size is
computed when other quantities are fixed.
plotCiNparDesign invisibly returns a list with components
x.var and y.var, giving coordinates of the points that
have been or would have been plotted.
See the help file for eqnpar.
See the help file for eqnpar.
# Look at the relationship between confidence level and sample size for
# a two-sided nonparametric confidence interval for the 90'th percentile.
dev.new()
plotCiNparDesign(p = 0.9)
#----------
# Plot sample size vs. quantile for various levels of confidence:
dev.new()
plotCiNparDesign(x.var = "p", y.var = "n", range.x.var = c(0.8, 0.95),
ylim = c(0, 60), main = "")
plotCiNparDesign(x.var = "p", y.var = "n", conf.level = 0.9, add = TRUE,
plot.col = 2, plot.lty = 2)
plotCiNparDesign(x.var = "p", y.var = "n", conf.level = 0.8, add = TRUE,
plot.col = 3, plot.lty = 3)
legend("topleft", c("95%", "90%", "80%"), lty = 1:3, col = 1:3,
lwd = 3 * par('cex'), bty = 'n')
title(main = paste("Sample Size vs. Quantile for ",
"Nonparametric CI for \nQuantile, with ",
"Various Confidence Levels", sep=""))
#==========
# Clean up
#---------
graphics.off()