can anyone help with this problem that I could not figure out? to perform 95% CI using boot but it outputs NaNs for original and bias for one column, e.g.fst_A_B_C_D$Fst_C_D, of the data. It works well with another two columns in the dataset. Below are the codes that I used. Many thanks in advance.
> mean_fst <- function(x,d){
return(mean(x[d]))
}
> str(fst_A_B_C_D$Fst_C_D)
num [1:8554] 0.836 0.759 0.793 0.663 0.644 ...
> bt5000_Fst_C_D=boot(fst_A_B_C_D$Fst_C_D,mean_fst,R=5000)
> bt5000_Fst_C_D
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = fst_A_B_C_D$Fst_C_D, statistic = mean_fst,
R = 5000)
Bootstrap Statistics :
original bias std. error
t1* NaN NaN 0.002661512
> plot(bt5000_Fst_C_D)
Error in if (t0 < rg[1L]) rg[1L] <- t0 else if (t0 > rg[2L]) rg[2L] <- t0 :
missing value where TRUE/FALSE needed