Why parametric bootstrapping bias and standard error are zero here?

Question

I'm performing parametric bootstrapping in R for a simple problem and getting Bias and Standard Error zero always. What am I doing wrong?

set.seed(12345)
df <- rnorm(n=10, mean = 0, sd = 1)

Boot.fun <- 
  function(data) {
    m1 <- mean(data)
    return(m1)
  }

Boot.fun(data = df)

library(boot)
out <- boot(df, Boot.fun, R = 20, sim = "parametric")
out
    PARAMETRIC BOOTSTRAP


Call:
boot(data = df, statistic = Boot.fun, R = 20, sim = "parametric")


Bootstrap Statistics :
      original  bias    std. error
t1* -0.1329441       0           0

Answer 1

You need to add line of code to do the sampling, ie.

Boot.fun <- 
    function(data) {
        data <- sample(data, replace=T)
        m1 <- ...

since you didn't supply a function to the argument rand.gen to generate random values. This is discussed in the documentation for ?boot. If sim = "parametric" and you don't supply a generating function, then the original data is passed to statistic and you need to sample in that function. Since your simulation was run on the same data, there is no standard error or bias.