When I use the fix that Arun K. provided to my earlier example, I wonder
how to find out where in the 999 bootstrap repetitions the value for the
actual data fits.
Here is the fixed code:
x <- 1:15
y <- c(2,4,1,3,5, 7,6, 9,10,8, 14, 13, 11, 15, 12)
x[3] <- NA; x[11] <- NA; x[8] <- NA
y[2] <- NA; y[8] <- NA; y[12] <- NA
cor(x,y,use="complete.obs",method="kendall")
library(boot)
tmpdf <- data.frame(x,y)
## corboot <- boot(tmpdf,
cor(x,y,use="complete.obs",method="kendall"),R=999)
cor1 <- function(x,y) {cor(x,y,use="complete.obs",method="kendall")}
corboot <- boot(tmpdf,cor1,R=999)
When I run that, I get
> corboot
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = tmpdf, statistic = cor1, R = 999)
Bootstrap Statistics :
original bias std. error
t1* 1.0000000 -1.0062026 0.2490860
t2* 0.8666667 -0.8694414 0.2491383
t2* is the estimate for the actual data. What is t1*? And again, how
do I find where in the distribution of the 999 reps does that true value
fall?
I would expect print(corboot) to give me more information, but it just
repeats that same output.
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