ple.plot {STAND} | R Documentation |
Plot PLE With Confidence Limits
Description
Plot the product limit estimate (PLE) of F(x) and
two-sided confidence limits (CLs) for left censored data. A horizontal line
corresponding to the Xp = 100pth percentile is added to the plot and
the nonparametric confidence limits for Xp are displayed in the title.
Usage
ple.plot(dd, gam = 0.95, p = 0.95, xlow = 0, xh = NA, ylow = 0, yh = 1,...)
Arguments
dd |
An n by 2 matrix or data frame with |
gam |
one-sided confidence level |
p |
probability for Xp the 100pth percentile. Default is 0.95 |
xlow |
minimum value on x axis. Default = 0 |
xh |
maximum value on the x axis. Default = maximum value of x |
ylow |
minimum value on y axis. Default = 0 |
yh |
maximum value on the y axis. Default = 1 |
... |
Additional parameters to plot |
Value
Data frame with columns
a |
value of jth detect (ordered) |
ple |
PLE of F(x) at a |
stder |
standard error of F(x) at a |
lower |
lower CL for PLE at a |
upper |
upper CL for PLE at a |
n |
number of detects or non-detects |
r |
number of detects equal to a |
Note
If the solid horizontal line does not intersect the lower
CL for the PLE, then the upper CL for Xp UX(p
,) is not defined.
Author(s)
E. L. Frome
See Also
See Also plekm
Examples
data(beTWA)
par( mfrow=c(1,2) )
ple.plot(beTWA) # plot the PLE of F(x) for the beTWA data
ple.plot(beTWA,ylow=0.8) # plot the upper right tail
# Lognormal ML estimates of 95th percentile and CLs
unlist(percentile.ml(beTWA))
# PLE estimates of 95th percentile and CLs
unlist(percentile.ple(beTWA))
#