Correctly Understanding the Use of the replicate() function - r

Question

I have the following function:
library(dplyr)
var_1 <- rnorm(100, 10, 10)
var_2 <- rnorm(100, 1, 10)
var_3 <- rnorm(100, 5, 10)
response <- rnorm(100, 1, 1)
my_data <- data.frame(var_1, var_2, var_3, response)
my_data$id <- 1:100
simulate <- function() {
results <- list()
results2 <- list()
for (i in 1:100) {
iteration_i <- i
sample_i <- my_data[sample(nrow(my_data), 10), ]
results_tmp <- data.frame(iteration_i, sample_i)
results[[i]] <- results_tmp
}
results_df <- do.call(rbind.data.frame, results)
test_1 <- data.frame(results_df %>%
group_by(id) %>%
filter(iteration_i == min(iteration_i)) %>%
distinct)
summary_file <- data.frame(test_1 %>%
group_by(iteration_i) %>%
summarise(Count=n()))
cumulative <- cumsum(summary_file$Count)
summary_file$Cumulative <- cumulative
summary_file$unobserved <- 100 - cumulative
return(summary_file)
}
When I call this function, I get the following output:
> head(simulate())
iteration_i Count Cumulative unobserved
1 1 10 10 90
2 2 7 17 83
3 3 10 27 73
4 4 5 32 68
5 5 7 39 61
6 6 8 47 53
I want to try to run this function 10 times and append all the results into a single file. I tried to do this using the "replicate()" function - but this is not working:
# Method 1 : Did not work
n_replicates = 10
iterations_required <- replicate(n_replicates, {
simulate()
})
# Method 2: Did not work
lapply(seq_len(10), simulate(1))
# Method 3: Did Not Work
library(purrr)
rerun(10, simulate(1))
# Method 4: Did Not Work
lapply(seq_len(10), simulate)
Ideally, I would like to get something like this:
# works fine!
results <- list()
for (i in 1:10) {
game_i <- i
s_i <- simulate()
results_tmp <- data.frame(game_i, s_i)
results[[i]] <- results_tmp
}
final_file <- do.call(rbind.data.frame, results)
My Question: Is there a reason that "Method 1, Method 2, Method 3, Method 4" were not working - could someone please show me how to fix this?

Answer 1

# Method 1 :
n_replicates = 10
iterations_required <- replicate(n_replicates, {
simulate()
}, simplify=FALSE)
# Method 2:
iterations_required<-lapply(seq_len(10), function(x) simulate(1))
# Method 4:
iterations_required<-lapply(seq_len(10), simulate)
# to merge into one data.frame
as.data.frame(data.table::rbindlist(iterations_required, idcol=TRUE))
Alternatively, if you modify your function to simulate(i), where i will be the first column in the output (interation index). Then you could use do.call(rbind.data.frame, lapply(seq_len(n_replicates), simulate))

Answer 2

replicate by default tries to simplify the result in a matrix. So the trick is actually just not to simplify.
n_replicates<- 10
iterations_required <- replicate(n_replicates, simulate(), simplify=FALSE)