Generate samples of size n and apply function in R?-CodePudding

I have the following code to generate my samples of size n, then want to perform an optimise function on the samples. I should get 1000 results from the optimise function but only get 1? Is there a way to perform the optimise function across the rows of 'x'

f2d <- function(n){
  x <- replicate(1000, rpois(n, 10))
  optimise(
    f = function(theta){ sum(dpois(x, theta, log = TRUE)) }, 
    interval = c(0,50), 
    maximum = TRUE
  )
}

CodePudding user response：

The function must be applied to each sample, so define an auxiliary function, fun, to be applied to each column. Then, call the function in an apply loop.

f2d <- function(n){
  fun <- function(y){
    optimise(
      function(theta){ sum(dpois(y, theta, log = TRUE)) }, 
      interval = c(0,50), 
      maximum = TRUE
    )
  }
  # apply the function to each poisson sample
  x <- replicate(1000, rpois(n, 10))
  apply(x, 2, fun)
}

set.seed(2021)
res <- f2d(10)
res <- do.call(rbind, res)

head(res)
#     maximum  objective
#[1,] 9.499999 -26.3231 
#[2,] 11.8     -25.62272
#[3,] 9.799998 -31.49774
#[4,] 10.4     -25.40647
#[5,] 10.4     -31.57375
#[6,] 9.899997 -27.67275