CODEWITHSUNDEEP
r
Killian Gavin
Killian Gavin

Reputation: 53

How would I loop my code to have 4 histograms instead of 1?

N <- 10000 ; maxbound = 20 

one_side_normal <- function(N) {
  f <- numeric(N);
  for (i in 1:N) {
    X = rexp(1,rate=1);
    uniform = runif(1);
    while (uniform>exp((-X^2)+X) ){
      X = rexp(1,rate=1);
      uniform=runif(1);
    }
    f[i] <- X
  }
  return(f)
}

The above code samples from a one sided normal distribution(sample =10000) using the acceptance-rejection method. How would I loop this code to run 4 separate times for samples of 10,100,1000 & 10000?

Upvotes: 0

Views: 18

Answers (1)

akrun
akrun

Reputation: 887048

We can use lapply to loop over the N values and apply the function. As there is only a single argument, we don't need any lambda function. It will return a list

lst1 <- lapply(c(10, 100, 1000, 10000), one_side_normal)

Another option is the classic for loop. To store the output, we can create a NULL list of fixed length i.e length of the vector of 'N' values. Then, loop over the sequence of 'N', apply the function and assign (<-) the output to the corresponding list element with that index

nvec <- c(10, 100, 1000, 10000)
lst1 <- vector('list', length(nvec))
for(i in seq_along(nvec)) lst1[[i]] <- one_side_normal(nvec[[i]])

Upvotes: 1

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