R calculate the standard error using bootstrap

Question

I have this array of values:

> df
[1] 2 0 0 2 2 0 0 1 0 1 2 1 0 1 3 0 0 1 1 0 0 0 2 1 2 1 3 1 0 0 0 1 1 2 0 1 3
[38] 1 0 2 1 1 2 2 1 2 2 2 1 1 1 2 1 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 0 0 0 0 0
[75] 0 0 0 0 0 1 1 0 1 1 1 1 3 1 3 0 1 2 2 1 2 3 1 0 0 1

I want to use package boot to calculate the standard error of the data. http://www.ats.ucla.edu/stat/r/faq/boot.htm

So, I used this command to pursue:

library(boot)
boot(df, mean, R=10)

and I got this error:

Error in mean.default(data, original, ...) : 
'trim' must be numeric of length one

Can someone help me figure out the problem? Thanks

Answer 1

If you are bootstrapping the mean you can do as follows:

set.seed(1)
library(boot)
x<-rnorm(100)
meanFunc <- function(x,i){mean(x[i])}
bootMean <- boot(x,meanFunc,100)
>bootMean

ORDINARY NONPARAMETRIC BOOTSTRAP


Call:
boot(data = x, statistic = meanFunc, R = 100)


Bootstrap Statistics :
     original      bias    std. error
t1* 0.1088874 0.002614105  0.07902184

If you just input the mean as an argument you will get the error like the one you got:

bootMean <- boot(x,mean,100)
Error in mean.default(data, original, ...) : 
  'trim' must be numeric of length one