I am trying to to calculate bootstrap confidence interval on a a index calculated from a vector of values, and if the index is significantly greater than 0 in R.

For example, the vector of length 6 = (0,0, 100, 30, 200,6) I calculate the index J= (var(vector)/mean(vector)^2) - (1/mean(vector))

I am trying to use a method of accelerated bootstrap from another paper that has done it in SAS, but I don't know what the R equivalent is? I dabbled with using boot.ci, but I wasn't sure how to specify it and if it was correct.

The bit from the paper I was referring to reads:

"We used the accelerated bootstrap (Dixon 2001, SAS) to estimate 95% confidence intervals for all aggregation indices and to test whether the parameter estimated by the index J differed significantly from 0 at alpha = 0.05"

I am trying to to calculate bootstrap confidence interval on an index calculated from a vector of values, and if the index is significantly greater than 0 in R.

For example, the vector of length 6: (0,0, 100, 30, 200,6).
And I calculate the index with:

J = (var(vector)/mean(vector)^2) - (1/mean(vector))

I am trying to use a method of accelerated bootstrap from another paper that has done it in SAS, but I don't know what the R equivalent is? I dabbled with using boot.ci, but I wasn't sure how to specify it and if it was correct.

The bit from the paper I was referring to reads:

"We used the accelerated bootstrap (Dixon 2001, SAS) to estimate 95% confidence intervals for all aggregation indices and to test whether the parameter estimated by the index J differed significantly from 0 at alpha = 0.05"