STAND (version 2.0)

ple.plot: Plot PLE With Confidence Limits

Description

Plot the product limit estimate (PLE) of F(x) and $100(2\gamma -1)\%$ 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 x (exposure) variable in column 1, and det = 0 for non-detect or 1 for detect in column 2

gam

one-sided confidence level $\gamma$. Default is 0.95

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 $\ge$ a

r

number of detects equal to a

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))
#