Vahid Mir - 1 year ago 153
R Question

# R calculate the standard error using bootstrap

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

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
``````
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