Folks,
I have this code fragment:
set.seed(1001)
x <- c(0.79211363702017, 0.940536712079832, 0.859757602692931,
0.82529998629531,
0.973451006822, 0.92378802164835, 0.996679563355802,
0.943347739494445, 0.992873542980045, 0.870624707845108,
0.935917364493788)
range(x)
# from 0.79 to 0.996
e <- function(x,d) {
median(x[d])
}
b <- boot(x, e, R=1000)
boot.ci(b)
The 95% confidence interval, as seen with `Normal' and `Basic'
calculations, has an upper bound of 1.0028 and 1.0121.
How is this possible? If I sample with replacement from values which
are all lower than 1, then any sample median of these bootstrap
samples should be lower than 1. The upper cutoff of the 95% confidence
interval should also be below 1.
Is this a bug in the boot package? Or should I be using `Percentile'
or `BCa' in this situation?
--
Ajay Shah http://www.mayin.org/ajayshah
ajays...@mayin.org http://ajayshahblog.blogspot.com
<*(:-? - wizard who doesn't know the answer.
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